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1
- ---
2
- license: apache-2.0
3
- pipeline_tag: text-to-speech
4
- library_name: transformers
5
- ---
6
- ## Step-Audio-EditX
7
 
8
- ✨ [Demo Page](https://stepaudiollm.github.io/step-audio-editx/) 
9
- | 🌟 [GitHub](https://github.com/stepfun-ai/Step-Audio-EditX) 
10
- | 📑 [Paper](https://arxiv.org/abs/2511.03601) 
11
-
12
- Check our open-source repository https://github.com/stepfun-ai/Step-Audio-EditX for more details!
 
 
13
 
14
  ## 🔥🔥🔥 News!!!
 
 
 
15
  * Nov 28, 2025: 🚀 New Model Release: Now supporting **`Japanese`** and **`Korean`** languages.
16
  * Nov 23, 2025: 📊 [Step-Audio-Edit-Benchmark](https://github.com/stepfun-ai/Step-Audio-Edit-Benchmark) Released!
17
  * Nov 19, 2025: ⚙️ We release a **new version** of our model, which **supports polyphonic pronunciation control** and improves the performance of emotion, speaking style, and paralinguistic editing.
 
 
 
18
 
19
- We are open-sourcing **Step-Audio-EditX**, a powerful **3B parameters** LLM-based audio model specialized in expressive and **iterative audio editing**.
20
- It excels at **editing emotion**, **speaking style**, and **paralinguistics**, and also features robust **zero-shot text-to-speech (TTS)** capabilities.
21
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
22
  ## Features
23
  - **Zero-Shot TTS**
24
- - Excellent zero-shot TTS cloning for `Mandarin`, `English`, `Sichuanese`, `Cantonese`, `Japanese` and `Korean`.
25
- - To use a dialect, just add a **`[Sichuanese]`**, **`[Cantonese]`** ,**`[Japanese]`**,**`[Korean]`** tag before your text.
 
 
26
 
 
27
  - **Emotion and Speaking Style Editing**
28
  - Remarkably effective iterative control over emotions and styles, supporting **dozens** of options for editing.
29
  - Emotion Editing : [ *Angry*, *Happy*, *Sad*, *Excited*, *Fearful*, *Surprised*, *Disgusted*, etc. ]
30
  - Speaking Style Editing: [ *Act_coy*, *Older*, *Child*, *Whisper*, *Serious*, *Generous*, *Exaggerated*, etc.]
31
- - Editing with more emotion and more speaking styles is on the way. **Get Ready!** 🚀
32
 
33
- - **Paralinguistic Editing**:
 
34
  - Precise control over 10 types of paralinguistic features for more natural, human-like, and expressive synthetic audio.
35
  - Supporting Tags:
36
- - [ *Breathing*, *Laughter*, *Suprise-oh*, *Confirmation-en*, *Uhm*, *Suprise-ah*, *Suprise-wa*, *Sigh*, *Question-ei*, *Dissatisfaction-hnn* ]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
37
 
38
  For more examples, see [demo page](https://stepaudiollm.github.io/step-audio-editx/).
39
 
 
 
 
 
 
 
 
 
 
40
  ## Model Usage
41
  ### 📜 Requirements
42
- The following table shows the requirements for running Step-Audio-EditX model:
43
 
44
  | Model | Parameters | Setting<br/>(sample frequency) | GPU Optimal Memory |
45
  |------------|------------|--------------------------------|----------------|
46
- | Step-Audio-EditX | 3B| 41.6Hz | 32 GB |
47
 
48
  * An NVIDIA GPU with CUDA support is required.
49
  * The model is tested on a single L40S GPU.
 
50
  * Tested operating system: Linux
51
 
52
  ### 🔧 Dependencies and Installation
53
- - Python >= 3.10.0 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html))
54
- - [PyTorch >= 2.4.1-cu121](https://pytorch.org/)
55
  - [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads)
56
 
57
  ```bash
58
  git clone https://github.com/stepfun-ai/Step-Audio-EditX.git
59
- conda create -n stepaudioedit python=3.10
60
- conda activate stepaudioedit
61
 
62
  cd Step-Audio-EditX
63
- pip install -r requirements.txt
 
64
 
65
  git lfs install
66
  git clone https://huggingface.co/stepfun-ai/Step-Audio-Tokenizer
67
  git clone https://huggingface.co/stepfun-ai/Step-Audio-EditX
 
68
 
69
  ```
70
 
@@ -77,7 +444,7 @@ where_you_download_dir
77
 
78
  #### Run with Docker
79
 
80
- You can set up the environment required for running Step-Audio using the provided Dockerfile.
81
 
82
  ```bash
83
  # build docker
@@ -90,43 +457,415 @@ docker run --rm --gpus all \
90
  -p 7860:7860 \
91
  step-audio-editx
92
  ```
93
-
94
-
95
- #### Launch Web Demo
96
- Start a local server for online inference.
97
- Assume you have one GPU with at least 32GB memory available and have already downloaded all the models.
98
-
99
- ```bash
100
- # Step-Audio-EditX demo
101
- python app.py --model-path where_you_download_dir --model-source local
102
- ```
103
-
104
  #### Local Inference Demo
105
  > [!TIP]
106
  > For optimal performance, keep audio under 30 seconds per inference.
107
 
108
  ```bash
109
  # zero-shot cloning
 
110
  python3 tts_infer.py \
111
  --model-path where_you_download_dir \
112
- --output-dir ./output \
113
- --prompt-text "your prompt text"\
114
- --prompt-audio your_prompt_audio_path \
115
- --generated-text "your target text" \
116
- --edit-type "clone"
 
 
 
 
 
 
 
 
 
 
117
 
118
  # edit
 
 
 
 
 
 
 
 
 
 
 
 
119
  python3 tts_infer.py \
120
  --model-path where_you_download_dir \
121
- --output-dir ./output \
122
- --prompt-text "your promt text" \
123
- --prompt-audio your_prompt_audio_path \
124
- --generated-text "" \ # for para-linguistic editing, you need to specify the generatedd text
125
  --edit-type "emotion" \
126
- --edit-info "sad" \
127
- --n-edit-iter 2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
128
  ```
129
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
130
 
131
  ## Citation
132
 
@@ -140,5 +879,19 @@ python3 tts_infer.py \
140
  primaryClass={cs.CL},
141
  url={https://arxiv.org/abs/2511.03601},
142
  }
 
 
 
 
 
 
 
 
 
 
 
 
 
143
 
144
- ```
 
 
1
+ # Step-Audio-EditX
2
+ <p align="center">
3
+ <img src="assets/logo.png" height=100>
4
+ </p>
 
 
5
 
6
+ <div align="center">
7
+ <a href="https://stepaudiollm.github.io/step-audio-editx/"><img src="https://img.shields.io/static/v1?label=Demo%20Page&message=Web&color=green"></a> &ensp;
8
+ <a href="https://arxiv.org/abs/2511.03601"><img src="https://img.shields.io/static/v1?label=Tech%20Report&message=Arxiv&color=red"></a> &ensp;
9
+ <a href="https://huggingface.co/stepfun-ai/Step-Audio-EditX"><img src="https://img.shields.io/static/v1?label=Step-Audio-EditX&message=HuggingFace&color=yellow"></a> &ensp;
10
+ <a href="https://modelscope.cn/models/stepfun-ai/Step-Audio-EditX"><img src="https://img.shields.io/static/v1?label=Step-Audio-EditX&message=ModelScope&color=blue"></a> &ensp;
11
+ <a href="https://huggingface.co/spaces/stepfun-ai/Step-Audio-EditX"><img src="https://img.shields.io/static/v1?label=Space%20Playground&message=HuggingFace&color=yellow"></a> &ensp;
12
+ </div>
13
 
14
  ## 🔥🔥🔥 News!!!
15
+ * Jan 23, 2026: 🌟 Training and inference for vLLM are now supported. Thanks to the vLLM team!
16
+ * Jan 23, 2026: 💻 We release the GRPO training code.
17
+ * Jan 23, 2026: 🧩 New Model Release: Now supporting more paralinguistic tags.
18
  * Nov 28, 2025: 🚀 New Model Release: Now supporting **`Japanese`** and **`Korean`** languages.
19
  * Nov 23, 2025: 📊 [Step-Audio-Edit-Benchmark](https://github.com/stepfun-ai/Step-Audio-Edit-Benchmark) Released!
20
  * Nov 19, 2025: ⚙️ We release a **new version** of our model, which **supports polyphonic pronunciation control** and improves the performance of emotion, speaking style, and paralinguistic editing.
21
+ * Nov 12, 2025: 📦 We release the **optimized inference code** and **model weights** of **Step-Audio-EditX** ([HuggingFace](https://huggingface.co/stepfun-ai/Step-Audio-EditX); [ModelScope](https://modelscope.cn/models/stepfun-ai/Step-Audio-EditX)) and **Step-Audio-Tokenizer**([HuggingFace](https://huggingface.co/stepfun-ai/Step-Audio-Tokenizer); [ModelScope](https://modelscope.cn/models/stepfun-ai/Step-Audio-Tokenizer))
22
+ * Nov 07, 2025: ✨ [Demo Page](https://stepaudiollm.github.io/step-audio-editx/) ; 🎮 [HF Space Playground](https://huggingface.co/spaces/stepfun-ai/Step-Audio-EditX)
23
+ * Nov 06, 2025: 👋 We release the technical report of [Step-Audio-EditX](https://arxiv.org/abs/2511.03601).
24
 
25
+ ## Introduction
26
+ We are open-sourcing Step-Audio-EditX, a powerful **3B-parameter** LLM-based **Reinforcement Learning** audio model specialized in expressive and iterative audio editing. It excels at editing emotion, speaking style, and paralinguistics, and also features robust zero-shot text-to-speech (TTS) capabilities.
27
 
28
+ ## 📑 Open-source Plan
29
+ - [x] Inference Code
30
+ - [x] Online demo (Gradio)
31
+ - [x] Step-Audio-Edit-Benchmark
32
+ - [x] Model Checkpoints
33
+ - [x] Step-Audio-Tokenizer
34
+ - [x] Step-Audio-EditX
35
+ - [x] Step-Audio-EditX-Int4
36
+ - [ ] Training Code
37
+ - [x] GRPO training
38
+ - [ ] SFT training
39
+ - [ ] PPO training
40
+ - [ ] ⏳ Feature Support Plan
41
+ - [ ] Editing
42
+ - [x] Polyphone pronunciation control
43
+ - [x] More paralinguistic tags ([Cough, Crying, Stress, etc.])
44
+ - [ ] Filler word removal
45
+ - [ ] Other Languages
46
+ - [x] Japanese, Korean
47
+ - [ ] Arabic, French, Russian, Spanish, etc.
48
+
49
  ## Features
50
  - **Zero-Shot TTS**
51
+ - Excellent zero-shot TTS cloning for Mandarin, English, Sichuanese, and Cantonese.
52
+ - To use dialect or other languages, just add a **`[Sichuanese]`** / **`[Cantonese]`** / **`[Japanese]`** / **`[Korean]`** tag before your text.
53
+ - 🔥 Polyphone pronunciation control, all you need to do is replace the polyphonic characters with pinyin.
54
+ - **[我也想过过过儿过过的生活]** -> **[我也想guo4guo4guo1儿guo4guo4的生活]**
55
 
56
+
57
  - **Emotion and Speaking Style Editing**
58
  - Remarkably effective iterative control over emotions and styles, supporting **dozens** of options for editing.
59
  - Emotion Editing : [ *Angry*, *Happy*, *Sad*, *Excited*, *Fearful*, *Surprised*, *Disgusted*, etc. ]
60
  - Speaking Style Editing: [ *Act_coy*, *Older*, *Child*, *Whisper*, *Serious*, *Generous*, *Exaggerated*, etc.]
61
+ - Editing with more emotion and more speaking styles is on the way. **Get Ready!** 🚀
62
 
63
+
64
+ - **Paralinguistic Editing**
65
  - Precise control over 10 types of paralinguistic features for more natural, human-like, and expressive synthetic audio.
66
  - Supporting Tags:
67
+ - [ *Breathing*, *Laughter*, *Surprise-oh*, *Confirmation-en*, *Uhm*, *Surprise-ah*, *Surprise-wa*, *Sigh*, *Question-ei*, *Dissatisfaction-hnn* ]
68
+
69
+ - **Available Tags**
70
+ <table>
71
+ <tr>
72
+ <td rowspan="8" style="vertical-align: middle; text-align:center;" align="center">emotion</td>
73
+ <td align="center"><b>happy</b></td>
74
+ <td align="center">Expressing happiness</td>
75
+ <td align="center"><b>angry</b></td>
76
+ <td align="center">Expressing anger</td>
77
+ </tr>
78
+ <tr>
79
+ <td align="center"><b>sad</b></td>
80
+ <td align="center">Expressing sadness</td>
81
+ <td align="center"><b>fear</b></td>
82
+ <td align="center">Expressing fear</td>
83
+ </tr>
84
+ <tr>
85
+ <td align="center"><b>surprised</b></td>
86
+ <td align="center">Expressing surprise</td>
87
+ <td align="center"><b>confusion</b></td>
88
+ <td align="center">Expressing confusion</td>
89
+ </tr>
90
+ <tr>
91
+ <td align="center"><b>empathy</b></td>
92
+ <td align="center">Expressing empathy and understanding</td>
93
+ <td align="center"><b>embarrass</b></td>
94
+ <td align="center">Expressing embarrassment</td>
95
+ </tr>
96
+ <tr>
97
+ <td align="center"><b>excited</b></td>
98
+ <td align="center">Expressing excitement and enthusiasm</td>
99
+ <td align="center"><b>depressed</b></td>
100
+ <td align="center">Expressing a depressed or discouraged mood</td>
101
+ </tr>
102
+ <tr>
103
+ <td align="center"><b>admiration</b></td>
104
+ <td align="center">Expressing admiration or respect</td>
105
+ <td align="center"><b>coldness</b></td>
106
+ <td align="center">Expressing coldness and indifference</td>
107
+ </tr>
108
+ <tr>
109
+ <td align="center"><b>disgusted</b></td>
110
+ <td align="center">Expressing disgust or aversion</td>
111
+ <td align="center"><b>humour</b></td>
112
+ <td align="center">Expressing humor or playfulness</td>
113
+ </tr>
114
+ <tr>
115
+ </tr>
116
+ <tr>
117
+ <td rowspan="17" style="vertical-align: middle; text-align:center;" align="center">speaking style</td>
118
+ <td align="center"><b>serious</b></td>
119
+ <td align="center">Speaking in a serious or solemn manner</td>
120
+ <td align="center"><b>arrogant</b></td>
121
+ <td align="center">Speaking in an arrogant manner</td>
122
+ </tr>
123
+ <tr>
124
+ <td align="center"><b>child</b></td>
125
+ <td align="center">Speaking in a childlike manner</td>
126
+ <td align="center"><b>older</b></td>
127
+ <td align="center">Speaking in an elderly-sounding manner</td>
128
+ </tr>
129
+ <tr>
130
+ <td align="center"><b>girl</b></td>
131
+ <td align="center">Speaking in a light, youthful feminine manner</td>
132
+ <td align="center"><b>pure</b></td>
133
+ <td align="center">Speaking in a pure, innocent manner</td>
134
+ </tr>
135
+ <tr>
136
+ <td align="center"><b>sister</b></td>
137
+ <td align="center">Speaking in a mature, confident feminine manner</td>
138
+ <td align="center"><b>sweet</b></td>
139
+ <td align="center">Speaking in a sweet, lovely manner</td>
140
+ </tr>
141
+ <tr>
142
+ <td align="center"><b>exaggerated</b></td>
143
+ <td align="center">Speaking in an exaggerated, dramatic manner</td>
144
+ <td align="center"><b>ethereal</b></td>
145
+ <td align="center">Speaking in a soft, airy, dreamy manner</td>
146
+ </tr>
147
+ <tr>
148
+ <td align="center"><b>whisper</b></td>
149
+ <td align="center">Speaking in a whispering, very soft manner</td>
150
+ <td align="center"><b>generous</b></td>
151
+ <td align="center">Speaking in a hearty, outgoing, and straight-talking manner</td>
152
+ </tr>
153
+ <tr>
154
+ <td align="center"><b>recite</b></td>
155
+ <td align="center">Speaking in a clear, well-paced, poetry-reading manner</td>
156
+ <td align="center"><b>act_coy</b></td>
157
+ <td align="center">Speaking in a sweet, playful, and endearing manner</td>
158
+ </tr>
159
+ <tr>
160
+ <td align="center"><b>warm</b></td>
161
+ <td align="center">Speaking in a warm, friendly manner</td>
162
+ <td align="center"><b>shy</b></td>
163
+ <td align="center">Speaking in a shy, timid manner</td>
164
+ </tr>
165
+ <tr>
166
+ <td align="center"><b>comfort</b></td>
167
+ <td align="center">Speaking in a comforting, reassuring manner</td>
168
+ <td align="center"><b>authority</b></td>
169
+ <td align="center">Speaking in an authoritative, commanding manner</td>
170
+ </tr>
171
+ <tr>
172
+ <td align="center"><b>chat</b></td>
173
+ <td align="center">Speaking in a casual, conversational manner</td>
174
+ <td align="center"><b>radio</b></td>
175
+ <td align="center">Speaking in a radio-broadcast manner</td>
176
+ </tr>
177
+ <tr>
178
+ <td align="center"><b>soulful</b></td>
179
+ <td align="center">Speaking in a heartfelt, deeply emotional manner</td>
180
+ <td align="center"><b>gentle</b></td>
181
+ <td align="center">Speaking in a gentle, soft manner</td>
182
+ </tr>
183
+ <tr>
184
+ <td align="center"><b>story</b></td>
185
+ <td align="center">Speaking in a narrative, audiobook-style manner</td>
186
+ <td align="center"><b>vivid</b></td>
187
+ <td align="center">Speaking in a lively, expressive manner</td>
188
+ </tr>
189
+ <tr>
190
+ <td align="center"><b>program</b></td>
191
+ <td align="center">Speaking in a show-host/presenter manner</td>
192
+ <td align="center"><b>news</b></td>
193
+ <td align="center">Speaking in a news broadcasting manner</td>
194
+ </tr>
195
+ <tr>
196
+ <td align="center"><b>advertising</b></td>
197
+ <td align="center">Speaking in a polished, high-end commercial voiceover manner</td>
198
+ <td align="center"><b>roar</b></td>
199
+ <td align="center">Speaking in a loud, deep, roaring manner</td>
200
+ </tr>
201
+ <tr>
202
+ <td align="center"><b>murmur</b></td>
203
+ <td align="center">Speaking in a quiet, low manner</td>
204
+ <td align="center"><b>shout</b></td>
205
+ <td align="center">Speaking in a loud, sharp, shouting manner</td>
206
+ </tr>
207
+ <tr>
208
+ <td align="center"><b>deeply</b></td>
209
+ <td align="center">Speaking in a deep and low-pitched tone</td>
210
+ <td align="center"><b>loudly</b></td>
211
+ <td align="center">Speaking in a loud and high-pitched tone</td>
212
+ </tr>
213
+ <tr>
214
+ </tr>
215
+ <tr>
216
+ </tr>
217
+ <tr>
218
+ <td rowspan="11" style="vertical-align: middle; text-align:center;" align="center">paralinguistic</td>
219
+ <td align="center"><b>[sigh]</b></td>
220
+ <td align="center">Sighing sound</td>
221
+ <td align="center"><b>[inhale]</b></td>
222
+ <td align="center">Inhaling sound</td>
223
+ </tr>
224
+
225
+ <tr>
226
+ <td align="center"><b>[laugh]</b></td>
227
+ <td align="center">Laughter sound</td>
228
+ <td align="center"><b>[chuckle]</b></td>
229
+ <td align="center">Chuckling sound</td>
230
+ </tr>
231
+
232
+ <tr>
233
+ <td align="center"><b>[exhale]</b></td>
234
+ <td align="center">Exhaling sound</td>
235
+ <td align="center"><b>[clears throat]</b></td>
236
+ <td align="center">Throat clearing sound</td>
237
+ </tr>
238
+
239
+ <tr>
240
+ <td align="center"><b>[snort]</b></td>
241
+ <td align="center">Snorting sound</td>
242
+ <td align="center"><b>[giggle]</b></td>
243
+ <td align="center">Giggling sound</td>
244
+ </tr>
245
+
246
+ <tr>
247
+ <td align="center"><b>[cough]</b></td>
248
+ <td align="center">Coughing sound</td>
249
+ <td align="center"><b>[breath]</b></td>
250
+ <td align="center">Breathing sound</td>
251
+ </tr>
252
+
253
+ <tr>
254
+ <td align="center"><b>[uhm]</b></td>
255
+ <td align="center">Hesitation sound: "Uhm"</td>
256
+ <td align="center"><b>[Confirmation-en]</b></td>
257
+ <td align="center">Confirming: "En"</td>
258
+ </tr>
259
+
260
+ <tr>
261
+ <td align="center"><b>[Surprise-oh]</b></td>
262
+ <td align="center">Expressing surprise: "Oh"</td>
263
+ <td align="center"><b>[Surprise-ah]</b></td>
264
+ <td align="center">Expressing surprise: "Ah"</td>
265
+ </tr>
266
+
267
+ <tr>
268
+ <td align="center"><b>[Surprise-wa]</b></td>
269
+ <td align="center">Expressing surprise: "Wa"</td>
270
+ <td align="center"><b>[Surprise-yo]</b></td>
271
+ <td align="center">Expressing surprise: "Yo"</td>
272
+ </tr>
273
+
274
+ <tr>
275
+ <td align="center"><b>[Dissatisfaction-hnn]</b></td>
276
+ <td align="center">Dissatisfied sound: "Hnn"</td>
277
+ <td align="center"><b>[Question-ei]</b></td>
278
+ <td align="center">Questioning: "Ei"</td>
279
+ </tr>
280
+
281
+ <tr>
282
+ <td align="center"><b>[Question-ah]</b></td>
283
+ <td align="center">Questioning: "Ah"</td>
284
+ <td align="center"><b>[Question-en]</b></td>
285
+ <td align="center">Questioning: "En"</td>
286
+ </tr>
287
+
288
+ <tr>
289
+ <td align="center"><b>[Question-yi]</b></td>
290
+ <td align="center">Questioning: "Yi"</td>
291
+ <td align="center"><b>[Question-oh]</b></td>
292
+ <td align="center">Questioning: "Oh"</td>
293
+ </tr>
294
+ </table>
295
+
296
+ ## Feature Requests & Wishlist
297
+ 💡 We welcome all ideas for new features! If you'd like to see a feature added to the project, please start a discussion in our [Discussions](https://github.com/stepfun-ai/Step-Audio-EditX/discussions) section.
298
+
299
+ We'll be collecting community feedback here and will incorporate popular suggestions into our future development plans. Thank you for your contribution!
300
+
301
+ ## Demos
302
+
303
+ <table>
304
+ <tr>
305
+ <th style="vertical-align : middle;text-align: center">Task</th>
306
+ <th style="vertical-align : middle;text-align: center">Text</th>
307
+ <th style="vertical-align : middle;text-align: center">Source</th>
308
+ <th style="vertical-align : middle;text-align: center">Edited</th>
309
+ </tr>
310
+
311
+ <tr>
312
+ <td align="center"> Emotion-Fear</td>
313
+ <td align="center"> 我总觉得,有人在跟着我,我能听到奇怪的脚步声。</td>
314
+ <td align="center">
315
+
316
+ [fear_zh_female_prompt.webm](https://github.com/user-attachments/assets/a088c059-032c-423f-81d6-3816ba347ff5)
317
+ </td>
318
+ <td align="center">
319
+
320
+ [fear_zh_female_output.webm](https://github.com/user-attachments/assets/917494ac-5913-4949-8022-46cf55ca05dd)
321
+ </td>
322
+ </tr>
323
+
324
+
325
+ <tr>
326
+ <td align="center"> Style-Whisper</td>
327
+ <td align="center"> 比如在工作间隙,做一些简单的伸展运动,放松一下身体,这样,会让你更有精力。</td>
328
+ <td align="center">
329
+
330
+ [whisper_prompt.webm](https://github.com/user-attachments/assets/ed9e22f1-1bac-417b-913a-5f1db31f35c9)
331
+ </td>
332
+ <td align="center">
333
+
334
+ [whisper_output.webm](https://github.com/user-attachments/assets/e0501050-40db-4d45-b380-8bcc309f0b5f)
335
+ </td>
336
+ </tr>
337
+
338
+ <tr>
339
+ <td align="center"> Style-Act_coy</td>
340
+ <td align="center"> 我今天想喝奶茶,可是不知道喝什么口味,你帮我选一下嘛,你选的都好喝~</td>
341
+ <td align="center">
342
+
343
+ [act_coy_prompt.webm](https://github.com/user-attachments/assets/74d60625-5b3c-4f45-becb-0d3fe7cc4b3f)
344
+ </td>
345
+ <td align="center">
346
+
347
+ [act_coy_output.webm](https://github.com/user-attachments/assets/b2f74577-56c2-4997-afd6-6bf47d15ea51)
348
+ </td>
349
+ </tr>
350
+
351
+
352
+ <tr>
353
+ <td align="center"> Paralinguistics</td>
354
+ <td align="center"> 你这次又忘记带钥匙了 [Dissatisfaction-hnn],真是拿你没办法。</td>
355
+ <td align="center">
356
+
357
+ [paralingustic_prompt.webm](https://github.com/user-attachments/assets/21e831a3-8110-4c64-a157-60e0cf6735f0)
358
+ </td>
359
+ <td align="center">
360
+
361
+ [paralingustic_output.webm](https://github.com/user-attachments/assets/a82f5a40-c6a3-409b-bbe6-271180b20d7b)
362
+ </td>
363
+ </tr>
364
+
365
+
366
+ <tr>
367
+ <td align="center"> Denoising</td>
368
+ <td align="center"> Such legislation was clarified and extended from time to time thereafter. No, the man was not drunk, he wondered how we got tied up with this stranger. Suddenly, my reflexes had gone. It's healthier to cook without sugar.</td>
369
+ <td align="center">
370
+
371
+ [denoising_prompt.webm](https://github.com/user-attachments/assets/70464bf4-ebde-44a3-b2a6-8c292333319b)
372
+ </td>
373
+ <td align="center">
374
+
375
+ [denoising_output.webm](https://github.com/user-attachments/assets/7cd0ae8d-1bf0-40fc-9bcd-f419bd4b2d21)
376
+ </td>
377
+ </tr>
378
+
379
+ <tr>
380
+ <td align="center"> Speed-Faster</td>
381
+ <td align="center"> 上次你说鞋子有点磨脚,我给你买了一双软软的鞋垫。</td>
382
+ <td align="center">
383
+
384
+ [speed_faster_prompt.webm](https://github.com/user-attachments/assets/db46609e-1b98-48d8-99c8-e166cfdfc6e3)
385
+ </td>
386
+ <td align="center">
387
+
388
+ [speed_faster_output.webm](https://github.com/user-attachments/assets/0fbc14ca-dd4a-4362-aadc-afe0629f4c9f)
389
+ </td>
390
+ </tr>
391
+
392
+ </table>
393
+
394
 
395
  For more examples, see [demo page](https://stepaudiollm.github.io/step-audio-editx/).
396
 
397
+ ## Model Download
398
+
399
+ | Models | 🤗 Hugging Face | ModelScope |
400
+ |-------|-------|-------|
401
+ | Step-Audio-EditX | [stepfun-ai/Step-Audio-EditX](https://huggingface.co/stepfun-ai/Step-Audio-EditX) | [stepfun-ai/Step-Audio-EditX](https://modelscope.cn/models/stepfun-ai/Step-Audio-EditX) |
402
+ | Step-Audio-EditX | [stepfun-ai/Step-Audio-EditX-AWQ-4bit](https://huggingface.co/stepfun-ai/Step-Audio-EditX-AWQ-4bit) | [stepfun-ai/Step-Audio-EditX-AWQ-4bit](https://modelscope.cn/models/stepfun-ai/Step-Audio-EditX-AWQ-4bit) |
403
+ | Step-Audio-Tokenizer | [stepfun-ai/Step-Audio-Tokenizer](https://huggingface.co/stepfun-ai/Step-Audio-Tokenizer) | [stepfun-ai/Step-Audio-Tokenizer](https://modelscope.cn/models/stepfun-ai/Step-Audio-Tokenizer) |
404
+
405
+
406
  ## Model Usage
407
  ### 📜 Requirements
408
+ The following table shows the requirements for running Step-Audio-EditX model (batch size = 1):
409
 
410
  | Model | Parameters | Setting<br/>(sample frequency) | GPU Optimal Memory |
411
  |------------|------------|--------------------------------|----------------|
412
+ | Step-Audio-EditX | 3B| 41.6Hz | 12 GB |
413
 
414
  * An NVIDIA GPU with CUDA support is required.
415
  * The model is tested on a single L40S GPU.
416
+ * 12GB is just a critical value, and 16GB GPU memory shoule be safer.
417
  * Tested operating system: Linux
418
 
419
  ### 🔧 Dependencies and Installation
420
+ - Python >= 3.12
421
+ - [PyTorch >= 2.9.1](https://pytorch.org/)
422
  - [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads)
423
 
424
  ```bash
425
  git clone https://github.com/stepfun-ai/Step-Audio-EditX.git
 
 
426
 
427
  cd Step-Audio-EditX
428
+ uv sync --refresh
429
+ source .venv/bin/activate
430
 
431
  git lfs install
432
  git clone https://huggingface.co/stepfun-ai/Step-Audio-Tokenizer
433
  git clone https://huggingface.co/stepfun-ai/Step-Audio-EditX
434
+ git clone https://huggingface.co/stepfun-ai/Step-Audio-EditX-AWQ-4bit/
435
 
436
  ```
437
 
 
444
 
445
  #### Run with Docker
446
 
447
+ You can set up the environment required for running Step-Audio-EditX using the provided Dockerfile.
448
 
449
  ```bash
450
  # build docker
 
457
  -p 7860:7860 \
458
  step-audio-editx
459
  ```
 
 
 
 
 
 
 
 
 
 
 
460
  #### Local Inference Demo
461
  > [!TIP]
462
  > For optimal performance, keep audio under 30 seconds per inference.
463
 
464
  ```bash
465
  # zero-shot cloning
466
+ # The path of the generated audio file is output/fear_zh_female_prompt_cloned.wav
467
  python3 tts_infer.py \
468
  --model-path where_you_download_dir \
469
+ --tokenizer-path where_you_download_dir \
470
+ --prompt-text "我总觉得,有人在跟着我,我能听到奇怪的脚步声。" \
471
+ --prompt-audio "examples/fear_zh_female_prompt.wav" \
472
+ --generated-text "可惜没有如果,已经发生的事情终究是发生了。" \
473
+ --edit-type "clone" \
474
+ --output-dir ./output
475
+
476
+ python3 tts_infer.py \
477
+ --model-path where_you_download_dir \
478
+ --tokenizer-path where_you_download_dir \
479
+ --prompt-text "His political stance was conservative, and he was particularly close to margaret thatcher." \
480
+ --prompt-audio "examples/zero_shot_en_prompt.wav" \
481
+ --generated-text "Underneath the courtyard is a large underground exhibition room which connects the two buildings. " \
482
+ --edit-type "clone" \
483
+ --output-dir ./output
484
 
485
  # edit
486
+ # There will be one or multiple wave files corresponding to each edit iteration, for example: output/fear_zh_female_prompt_edited_iter1.wav, output/fear_zh_female_prompt_edited_iter2.wav, ...
487
+ # emotion; fear
488
+ python3 tts_infer.py \
489
+ --model-path where_you_download_dir \
490
+ --tokenizer-path where_you_download_dir \
491
+ --prompt-text "我总觉得,有人在跟着我,我能听到奇怪的脚步声。" \
492
+ --prompt-audio "examples/fear_zh_female_prompt.wav" \
493
+ --edit-type "emotion" \
494
+ --edit-info "fear" \
495
+ --output-dir ./output
496
+
497
+ # emotion; happy
498
  python3 tts_infer.py \
499
  --model-path where_you_download_dir \
500
+ --tokenizer-path where_you_download_dir \
501
+ --prompt-text "You know, I just finished that big project and feel so relieved. Everything seems easier and more colorful, what a wonderful feeling!" \
502
+ --prompt-audio "examples/en_happy_prompt.wav" \
 
503
  --edit-type "emotion" \
504
+ --edit-info "happy" \
505
+ --output-dir ./output
506
+
507
+ # style; whisper
508
+ # for style whisper, the edit iteration num should be set bigger than 1 to get better results.
509
+ python3 tts_infer.py \
510
+ --model-path where_you_download_dir \
511
+ --tokenizer-path where_you_download_dir \
512
+ --prompt-text "比如在工作间隙,做一些简单的伸展运动,放松一下身体,这样,会让你更有精力." \
513
+ --prompt-audio "examples/whisper_prompt.wav" \
514
+ --edit-type "style" \
515
+ --edit-info "whisper" \
516
+ --output-dir ./output
517
+
518
+ # paraliguistic
519
+ # supported tags, Breathing, Laughter, Surprise-oh, Confirmation-en, Uhm, Surprise-ah, Surprise-wa, Sigh, Question-ei, Dissatisfaction-hnn
520
+ python3 tts_infer.py \
521
+ --model-path where_you_download_dir \
522
+ --tokenizer-path where_you_download_dir \
523
+ --prompt-text "我觉得这个计划大概是可行的,不过还需要再仔细考虑一下。" \
524
+ --prompt-audio "examples/paralingustic_prompt.wav" \
525
+ --generated-text "我觉得这个计划大概是可行的,[Uhm]不过还需要再仔细考虑一下。" \
526
+ --edit-type "paralinguistic" \
527
+ --output-dir ./output
528
+
529
+ # denoise
530
+ # Prompt text is not needed.
531
+ python3 tts_infer.py \
532
+ --model-path where_you_download_dir \
533
+ --tokenizer-path where_you_download_dir \
534
+ --prompt-audio "examples/denoise_prompt.wav"\
535
+ --edit-type "denoise" \
536
+ --output-dir ./output
537
+
538
+ # vad
539
+ # Prompt text is not needed.
540
+ python3 tts_infer.py \
541
+ --model-path where_you_download_dir \
542
+ --tokenizer-path where_you_download_dir \
543
+ --prompt-audio "examples/vad_prompt.wav" \
544
+ --edit-type "vad" \
545
+ --output-dir ./output
546
+
547
+ # speed
548
+ # supported edit-info: faster, slower, more faster, more slower
549
+ python3 tts_infer.py \
550
+ --model-path where_you_download_dir \
551
+ --tokenizer-path where_you_download_dir \
552
+ --prompt-text "上次你说鞋子有点磨脚,我给你买了一双软软的鞋垫。" \
553
+ --prompt-audio "examples/speed_prompt.wav" \
554
+ --edit-type "speed" \
555
+ --edit-info "more faster" \
556
+ --output-dir ./output
557
+
558
+ ```
559
+
560
+
561
+
562
+ #### Launch Web Demo
563
+ Start a local server for online inference.
564
+ Assume you have one GPU with at least 12GB memory available and have already downloaded all the models.
565
+
566
+ ```bash
567
+ # Standard launch
568
+ python app.py --model-path where_you_download_dir --tokenizer-path where_you_download_dir --model-source local
569
+
570
+ # Using pre-quantized AWQ 4-bit models, memory-efficient mode (for limited GPU memory, ~6-8GB usage)
571
+ python app.py \
572
+ --model-path path/to/quantized/model \
573
+ --tokenizer-path where_you_download_dir \
574
+ --model-source local \
575
+ --gpu-memory-utilization 0.1 \
576
+ --enforce-eager \
577
+ --max-num-seqs 1 \
578
+ --cosyvoice-dtype bfloat16 \
579
+ --no-cosyvoice-cuda-graph
580
+
581
+ ```
582
+
583
+ ##### Available Parameters
584
+
585
+ | Parameter | Default | Description |
586
+ |-----------|---------|-------------|
587
+ | `--model-path` | (required) | Path to the model directory |
588
+ | `--model-source` | `auto` | Model source: `auto`, `local`, `modelscope`, `huggingface` |
589
+ | `--gpu-memory-utilization` | `0.5` | GPU memory ratio for vLLM KV cache (0.0-1.0) |
590
+ | `--max-model-len` | `3072` | Maximum sequence length, affects KV cache size |
591
+ | `--enforce-eager` | `True` | Disable vLLM CUDA Graphs (saves ~0.5GB memory) |
592
+ | `--max-num-seqs` | `1` | Maximum concurrent sequences (vLLM default: 256, lower = less memory) |
593
+ | `--dtype` | `bfloat16` | Model dtype: `float16`, `bfloat16` |
594
+ | `--quantization` | `None` | Quantization method: `awq`, `gptq`, `fp8` |
595
+ | `--cosyvoice-dtype` | `bfloat16` | CosyVoice vocoder dtype: `float32`, `bfloat16`, `float16` |
596
+ | `--no-cosyvoice-cuda-graph` | `False` | Disable CosyVoice CUDA Graphs (saves memory) |
597
+ | `--enable-auto-transcribe` | `False` | Enable automatic audio transcription |
598
+
599
+ ##### Memory Usage Guide
600
+
601
+ | Configuration | Estimated GPU Memory | Use Case |
602
+ |--------------|---------------------|----------|
603
+ | Standard (defaults) | ~12-15 GB | Best quality and speed |
604
+ | Memory-efficient | ~6-8 GB | Limited GPU memory, some quality trade-off |
605
+ | AWQ 4-bit quantized | ~8-10 GB | Good balance of quality and memory |
606
+
607
+ ## Training
608
+ Please refer to script/ReadMe.md
609
+
610
+ ### 🔄 Model Quantization (Optional)
611
+
612
+ For users with limited GPU memory, you can create quantized versions of the model to reduce memory requirements:
613
+
614
+ ```bash
615
+ # Create an AWQ 4-bit quantized model
616
+ python quantization/awq_quantize.py --model_path path/to/Step-Audio-EditX
617
+
618
+ # Advanced quantization options
619
+ python quantization/awq_quantize.py
620
  ```
621
 
622
+ For detailed quantization options and parameters, see [quantization/README.md](quantization/README.md).
623
+
624
+
625
+ ## Technical Details
626
+ <img src="assets/architechture.png" width=900>
627
+ Step-Audio-EditX comprises three primary components:
628
+
629
+ - A dual-codebook audio tokenizer, which converts reference or input audio into discrete tokens.
630
+ - An audio LLM that generates dual-codebook token sequences.
631
+ - An audio decoder, which converts the dual-codebook token sequences predicted by the audio LLM back into audio waveforms using a flow matching approach.
632
+
633
+ Audio-Edit enables iterative control over emotion and speaking style across all voices, leveraging large-margin data during SFT and PPO training.
634
+
635
+ ## Evaluation
636
+
637
+ ### Comparison between Step-Audio-EditX and Closed-Source models.
638
+
639
+ - Step-Audio-EditX demonstrates superior performance over Minimax and Doubao in both zero-shot cloning and emotion control.
640
+ - Emotion editing of Step-Audio-EditX significantly improves the emotion-controlled audio outputs of all three models after just one iteration. With further iterations, their overall performance continues to improve.
641
+
642
+ <div align="center">
643
+ <img src="assets/emotion-eval.png" width=800 >
644
+ </div>
645
+
646
+ ### Generalization on Closed-Source Models.
647
+ - For emotion and speaking style editing, the built-in voices of leading closed-source systems possess considerable in-context capabilities, allowing them to partially convey the emotions in the text. After a single editing round with Step-Audio-EditX, the emotion and style accuracy across all voice models exhibited significant improvement. Further enhancement was observed over the next two iterations, robustly demonstrating our model's strong generalization.
648
+
649
+ - For paralinguistic editing, after editing with Step-Audio-EditX, the performance of paralinguistic reproduction is comparable to that achieved by the built-in voices of closed-source models when synthesizing native paralinguistic content directly. (**sub** means replacement of paralinguistic tags with native words)
650
+
651
+
652
+ <div align="center">
653
+
654
+ <table border="1" cellspacing="0" cellpadding="5" style="border-collapse: collapse; font-family: sans-serif; width: auto;">
655
+ <caption><b>Table: Generalization of Emotion, Speaking Style, and Paralinguistic Editing on Closed-Source Models.</b></caption>
656
+ <thead>
657
+ <tr>
658
+ <th rowspan="2" align="center" style="vertical-align: bottom;">Language</th>
659
+ <th rowspan="2" align="center" style="vertical-align: bottom;">Model</th>
660
+ <th colspan="4" style="border-bottom: 1px solid black;">Emotion &uarr;</th>
661
+ <th colspan="4" style="border-bottom: 1px solid black;">Speaking Style &uarr;</th>
662
+ <th colspan="3" style="border-bottom: 1px solid black; border-left: 1px solid black;">Paralinguistic &uarr;</th>
663
+ </tr>
664
+ <tr>
665
+ <th>Iter<sub>0</sub></th>
666
+ <th>Iter<sub>1</sub></th>
667
+ <th>Iter<sub>2</sub></th>
668
+ <th>Iter<sub>3</sub></th>
669
+ <th style="border-left: 1px solid #ccc;">Iter<sub>0</sub></th>
670
+ <th>Iter<sub>1</sub></th>
671
+ <th>Iter<sub>2</sub></th>
672
+ <th>Iter<sub>3</sub></th>
673
+ <th style="border-left: 1px solid black;">Iter<sub>0</sub></th>
674
+ <th>sub</th>
675
+ <th>Iter<sub>1</sub></th>
676
+ </tr>
677
+ </thead>
678
+ <tbody>
679
+ <tr>
680
+ <td rowspan="4" align="center" style="font-weight: bold; vertical-align: middle;">Chinese</td>
681
+ <td align="left">MiniMax-2.6-hd</td>
682
+ <td align="center">71.6</td>
683
+ <td align="center">78.6</td>
684
+ <td align="center">81.2</td>
685
+ <td align="center"><b>83.4</b></td>
686
+ <td align="center" style="border-left: 1px solid #ccc;">36.7</td>
687
+ <td align="center">58.8</td>
688
+ <td align="center">63.1</td>
689
+ <td align="center"><b>67.3</b></td>
690
+ <td align="center" style="border-left: 1px solid black;">1.73</td>
691
+ <td align="center">2.80</td>
692
+ <td align="center">2.90</td>
693
+ </tr>
694
+ <tr>
695
+ <td align="left">Doubao-Seed-TTS-2.0</td>
696
+ <td align="center">67.4</td>
697
+ <td align="center">77.8</td>
698
+ <td align="center">80.6</td>
699
+ <td align="center"><b>82.8</b></td>
700
+ <td align="center" style="border-left: 1px solid #ccc;">38.2</td>
701
+ <td align="center">60.2</td>
702
+ <td align="center"><b>65.0</b></td>
703
+ <td align="center">64.9</td>
704
+ <td align="center" style="border-left: 1px solid black;">1.67</td>
705
+ <td align="center">2.81</td>
706
+ <td align="center">2.90</td>
707
+ </tr>
708
+ <tr>
709
+ <td align="left">GPT-4o-mini-TTS</td>
710
+ <td align="center">62.6</td>
711
+ <td align="center">76.0</td>
712
+ <td align="center">77.0</td>
713
+ <td align="center"><b>81.8</b></td>
714
+ <td align="center" style="border-left: 1px solid #ccc;">45.9</td>
715
+ <td align="center">64.0</td>
716
+ <td align="center">65.7</td>
717
+ <td align="center"><b>69.7</b></td>
718
+ <td align="center" style="border-left: 1px solid black;">1.71</td>
719
+ <td align="center">2.88</td>
720
+ <td align="center">2.93</td>
721
+ </tr>
722
+ <tr style="border-bottom: 1px solid black;">
723
+ <td align="left">ElevenLabs-v2</td>
724
+ <td align="center">60.4</td>
725
+ <td align="center">74.6</td>
726
+ <td align="center">77.4</td>
727
+ <td align="center"><b>79.2</b></td>
728
+ <td align="center" style="border-left: 1px solid #ccc;">43.8</td>
729
+ <td align="center">63.3</td>
730
+ <td align="center">69.7</td>
731
+ <td align="center"><b>70.8</b></td>
732
+ <td align="center" style="border-left: 1px solid black;">1.70</td>
733
+ <td align="center">2.71</td>
734
+ <td align="center">2.92</td>
735
+ </tr>
736
+ <tr>
737
+ <td rowspan="4" align="center" style="font-weight: bold; vertical-align: middle;">English</td>
738
+ <td align="left">MiniMax-2.6-hd</td>
739
+ <td align="center">55.0</td>
740
+ <td align="center">64.0</td>
741
+ <td align="center">64.2</td>
742
+ <td align="center"><b>66.4</b></td>
743
+ <td align="center" style="border-left: 1px solid #ccc;">51.9</td>
744
+ <td align="center">60.3</td>
745
+ <td align="center">62.3</td>
746
+ <td align="center"><b>64.3</b></td>
747
+ <td align="center" style="border-left: 1px solid black;">1.72</td>
748
+ <td align="center">2.87</td>
749
+ <td align="center">2.88</td>
750
+ </tr>
751
+ <tr>
752
+ <td align="left">Doubao-Seed-TTS-2.0</td>
753
+ <td align="center">53.8</td>
754
+ <td align="center">65.8</td>
755
+ <td align="center">65.8</td>
756
+ <td align="center"><b>66.2</b></td>
757
+ <td align="center" style="border-left: 1px solid #ccc;">47.0</td>
758
+ <td align="center">62.0</td>
759
+ <td align="center"><b>62.7</b></td>
760
+ <td align="center">62.3</td>
761
+ <td align="center" style="border-left: 1px solid black;">1.72</td>
762
+ <td align="center">2.75</td>
763
+ <td align="center">2.92</td>
764
+ </tr>
765
+ <tr>
766
+ <td align="left">GPT-4o-mini-TTS</td>
767
+ <td align="center">56.8</td>
768
+ <td align="center">61.4</td>
769
+ <td align="center">64.8</td>
770
+ <td align="center"><b>65.2</b></td>
771
+ <td align="center" style="border-left: 1px solid #ccc;">52.3</td>
772
+ <td align="center">62.3</td>
773
+ <td align="center">62.4</td>
774
+ <td align="center"><b>63.4</b></td>
775
+ <td align="center" style="border-left: 1px solid black;">1.90</td>
776
+ <td align="center">2.90</td>
777
+ <td align="center">2.88</td>
778
+ </tr>
779
+ <tr style="border-bottom: 1px solid black;">
780
+ <td align="left">ElevenLabs-v2</td>
781
+ <td align="center">51.0</td>
782
+ <td align="center">61.2</td>
783
+ <td align="center">64.0</td>
784
+ <td align="center"><b>65.2</b></td>
785
+ <td align="center" style="border-left: 1px solid #ccc;">51.0</td>
786
+ <td align="center">62.1</td>
787
+ <td align="center">62.6</td>
788
+ <td align="center"><b>64.0</b></td>
789
+ <td align="center" style="border-left: 1px solid black;">1.93</td>
790
+ <td align="center">2.87</td>
791
+ <td align="center">2.88</td>
792
+ </tr>
793
+ <tr>
794
+ <td rowspan="4" align="center" style="font-weight: bold; vertical-align: middle;">Average</td>
795
+ <td align="left">MiniMax-2.6-hd</td>
796
+ <td align="center">63.3</td>
797
+ <td align="center">71.3</td>
798
+ <td align="center">72.7</td>
799
+ <td align="center"><b>74.9</b></td>
800
+ <td align="center" style="border-left: 1px solid #ccc;">44.2</td>
801
+ <td align="center">59.6</td>
802
+ <td align="center">62.7</td>
803
+ <td align="center"><b>65.8</b></td>
804
+ <td align="center" style="border-left: 1px solid black;">1.73</td>
805
+ <td align="center">2.84</td>
806
+ <td align="center">2.89</td>
807
+ </tr>
808
+ <tr>
809
+ <td align="left">Doubao-Seed-TTS-2.0</td>
810
+ <td align="center">60.6</td>
811
+ <td align="center">71.8</td>
812
+ <td align="center">73.2</td>
813
+ <td align="center"><b>74.5</b></td>
814
+ <td align="center" style="border-left: 1px solid #ccc;">42.6</td>
815
+ <td align="center">61.1</td>
816
+ <td align="center"><b>63.9</b></td>
817
+ <td align="center">63.6</td>
818
+ <td align="center" style="border-left: 1px solid black;">1.70</td>
819
+ <td align="center">2.78</td>
820
+ <td align="center">2.91</td>
821
+ </tr>
822
+ <tr>
823
+ <td align="left">GPT-4o-mini-TTS</td>
824
+ <td align="center">59.7</td>
825
+ <td align="center">68.7</td>
826
+ <td align="center">70.9</td>
827
+ <td align="center"><b>73.5</b></td>
828
+ <td align="center" style="border-left: 1px solid #ccc;">49.1</td>
829
+ <td align="center">63.2</td>
830
+ <td align="center">64.1</td>
831
+ <td align="center"><b>66.6</b></td>
832
+ <td align="center" style="border-left: 1px solid black;">1.81</td>
833
+ <td align="center">2.89</td>
834
+ <td align="center">2.90</td>
835
+ </tr>
836
+ <tr>
837
+ <td align="left">ElevenLabs-v2</td>
838
+ <td align="center">55.7</td>
839
+ <td align="center">67.9</td>
840
+ <td align="center">70.7</td>
841
+ <td align="center"><b>72.2</b></td>
842
+ <td align="center" style="border-left: 1px solid #ccc;">47.4</td>
843
+ <td align="center">62.7</td>
844
+ <td align="center">66.1</td>
845
+ <td align="center"><b>67.4</b></td>
846
+ <td align="center" style="border-left: 1px solid black;">1.82</td>
847
+ <td align="center">2.79</td>
848
+ <td align="center">2.90</td>
849
+ </tr>
850
+ </tbody>
851
+ </table>
852
+
853
+ </div>
854
+
855
+
856
+ ## Acknowledgements
857
+
858
+ Part of the code and data for this project comes from:
859
+ * [CosyVoice](https://github.com/FunAudioLLM/CosyVoice)
860
+ * [transformers](https://github.com/huggingface/transformers)
861
+ * [FunASR](https://github.com/modelscope/FunASR)
862
+ * [NVSpeech](https://huggingface.co/datasets/amphion/Emilia-NV)
863
+ * [vllm](https://github.com/vllm-project/vllm)
864
+
865
+ Thank you to all the open-source projects for their contributions to this project!
866
+
867
+ ## License Agreement
868
+ + The code in this open-source repository is licensed under the [Apache 2.0](LICENSE) License.
869
 
870
  ## Citation
871
 
 
879
  primaryClass={cs.CL},
880
  url={https://arxiv.org/abs/2511.03601},
881
  }
882
+ ```
883
+
884
+
885
+ ## ⚠️ Usage Disclaimer
886
+ - Do not use this model for any unauthorized activities, including but not limited to:
887
+ - Voice cloning without permission
888
+ - Identity impersonation
889
+ - Fraud
890
+ - Deepfakes or any other illegal purposes
891
+ - Ensure compliance with local laws and regulations, and adhere to ethical guidelines when using this model.
892
+ - The model developers are not responsible for any misuse or abuse of this technology.
893
+
894
+ We advocate for responsible generative AI research and urge the community to uphold safety and ethical standards in AI development and application. If you have any concerns regarding the use of this model, please feel free to contact us.
895
 
896
+ ## Star History
897
+ [![Star History Chart](https://api.star-history.com/svg?repos=stepfun-ai/Step-Audio-EditX&type=Date)](https://star-history.com/#stepfun-ai/Step-Audio-EditX&Date)