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+Tencent is pleased to support the open source community by making StableToken available.
+
+Copyright (C) 2026 Tencent.  All rights reserved. 
+
+The open-source software and/or models included in this distribution may have been modified by Tencent (“Tencent Modifications”). All Tencent Modifications are Copyright (C) Tencent.
+
+StableToken is licensed under the License Terms of StableToken, except for the third-party components listed below, which remain licensed under their respective original terms. StableToken does not impose any additional restrictions beyond those specified in the original licenses of these third-party components. Users are required to comply with all applicable terms and conditions of the original licenses and to ensure that the use of these third-party components conforms to all relevant laws and regulations.
+
+For the avoidance of doubt, StableToken refers solely to inference code, parameters, and weights made publicly available by Tencent in accordance with the License Terms of StableToken. 
+
+Terms of the License Terms of StableToken:
+--------------------------------------------------------------------
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+1. StableToken IS NOT INTENDED FOR USE WITHIN THE EUROPEAN UNION.
+
+2. The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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+Dependencies and Licenses:
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+This open-source project, StableToken, builds upon the following open-source models and/or software components, each of which remains licensed under its original license. Certain models or software may include modifications made by Tencent (“Tencent Modifications”), which are Copyright (C) Tencent.
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+In case you believe there have been errors in the attribution below, you may submit the concerns to us for review and correction.
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+
+Open Source Model Licensed under the Apache-2.0:
+--------------------------------------------------------------------
+1. whisper
+Copyright (c) openai/whisper-large-v3 original author and authors
+Please note this model has been modified by Tencent in this distribution.
+
+ 
+
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+--------------------------------------------------------------------
+1. Code of GLM-4-Voice
+Copyright 2024 GLM-4-Voice Model Team @ Zhipu AI
+Please note this software has been modified by Tencent in this distribution.
+
+Terms of the Apache-2.0:
+--------------------------------------------------------------------
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+                                 Apache License
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+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+   1. Definitions.
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+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
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+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright 2024 GLM-4-Voice Model Team @ Zhipu AI
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

README.md

@@ -0,0 +1,106 @@
+---
+license: other
+license_name: license-term-of-stabletoken
+language:
+- en
+- zh
+tags:
+- speech tokenizer
+---
+# StableToken (ICLR 2026)
+
+**StableToken** is a noise-robust semantic speech tokenizer that performs discrete speech representation learning, achieving state-of-the-art stability in noisy environments.
+
+📄 [Paper](https://arxiv.org/abs/2509.22220) | 💻 [GitHub](https://github.com/Tencent/StableToken)
+
+For code and more detailed information, please refer to the corresponding [GitHub repository](https://github.com/Tencent/StableToken).
+
+## Model Details
+
+| Attribute | Value |
+|:----------|:------|
+| Frame Rate | 25 Hz |
+| Codebook Size | 8,192 |
+| BPS (Bits Per Second) | 325 |
+
+## Quick Start
+
+To use StableToken, please clone the official repository and install dependencies.
+
+### Installation
+
+```bash
+git clone --recursive https://github.com/Tencent/StableToken.git
+cd StableToken && pip install -r requirements.txt
+```
+
+### Inference
+
+```python
+import os
+from huggingface_hub import snapshot_download
+from transformers import WhisperFeatureExtractor
+from src.model.modeling_whisper import WhisperLFQEncoder
+from src.utils.flow_inference import AudioDecoder
+from src.utils.utils import extract_speech_token, speech_token_to_wav
+
+# 1. Download & Load Models
+model_dir = snapshot_download("tencent/StableToken")
+
+# Load Tokenizer
+tokenizer = WhisperLFQEncoder.from_pretrained(os.path.join(model_dir, "tokenizer")).eval().cuda()
+feature_extractor = WhisperFeatureExtractor.from_pretrained(os.path.join(model_dir, "tokenizer"))
+
+# Load Decoder
+decoder = AudioDecoder(
+    config_path=os.path.join(model_dir, "decoder", "config.yaml"),
+    flow_ckpt_path=os.path.join(model_dir, "decoder", "flow.pt"),
+    hift_ckpt_path=os.path.join(model_dir, "decoder", "hift.pt"),
+    device="cuda"
+)
+
+# 2. Tokenize
+tokens = extract_speech_token(tokenizer, feature_extractor, ["/path/to/audio.wav"], device="cuda")[0]
+
+# 3. Reconstruct
+tts_speech, sampling_rate = speech_token_to_wav(decoder, tokens)
+```
+
+## Performance
+
+StableToken achieves **60% lower UED** (Unit Edit Distance) than best existing supervised semantic tokenizers.
+
+### Noise Robustness (UED ↓)
+
+| Model | Frame Rate | Codebook Size | UED (%, ↓) |
+|:---|:---:|:---:|:---:|
+| [GLM-4-Voice](https://github.com/zai-org/GLM-4-Voice) | 12.5Hz | 16,384 | 31.10 |
+| [$\mathcal{S}^3$ Tokenizer](https://github.com/FunAudioLLM/CosyVoice) | 25Hz | 4,096 | 26.17 |
+| [CosyVoice2](https://github.com/FunAudioLLM/CosyVoice) | 25Hz | 6,561 | 38.66 |
+| **StableToken** | 25Hz | 8,192 | **10.17** 🏆 |
+
+### Reconstruction Quality
+
+Measurements on LibriSpeech (LS) and SEED benchmarks.
+
+| Benchmark | WER (↓) | MOS (↑) |
+|:----------|:-------:|:-------:|
+| LibriSpeech Clean | **3.84** | **4.09** |
+| LibriSpeech Other | **7.99** | 3.83 |
+| SEED-En | **3.44** | 4.01 |
+| SEED-Zh | **2.62** | **4.18** |
+
+## Citation
+
+```bibtex
+@article{song2025stabletoken,
+  title={StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs},
+  author={Song, Yuhan and Zhang, Linhao and Wu, Chuhan and Liu, Aiwei and Jia, Wei and Wang, Houfeng and Zhou, Xiao},
+  journal={arXiv preprint arXiv:2509.22220},
+  year={2025}
+}
+```
+
+## License
+
+This project is licensed under the [License Term of StableToken](LICENSE).

decoder/config.yaml

@@ -0,0 +1,130 @@
+# set random seed, so that you may reproduce your result.
+__set_seed1: !apply:random.seed [1986]
+__set_seed2: !apply:numpy.random.seed [1986]
+__set_seed3: !apply:torch.manual_seed [1986]
+__set_seed4: !apply:torch.cuda.manual_seed_all [1986]
+
+# fixed params
+sample_rate: 22050
+text_encoder_input_size: 512
+llm_input_size: 1024
+llm_output_size: 1024
+spk_embed_dim: 192
+
+# model params
+# for all class/function included in this repo, we use !<name> or !<new> for intialization, so that user may find all corresponding class/function according to one single yaml.
+# for system/third_party class/function, we do not require this.
+llm: !new:cosyvoice.llm.llm.TransformerLM
+    text_encoder_input_size: !ref <text_encoder_input_size>
+    llm_input_size: !ref <llm_input_size>
+    llm_output_size: !ref <llm_output_size>
+    text_token_size: 51866
+    speech_token_size: 4096
+    length_normalized_loss: True
+    lsm_weight: 0
+    spk_embed_dim: !ref <spk_embed_dim>
+    text_encoder: !new:cosyvoice.transformer.encoder.ConformerEncoder
+        input_size: !ref <text_encoder_input_size>
+        output_size: 1024
+        attention_heads: 8
+        linear_units: 2048
+        num_blocks: 3
+        dropout_rate: 0.1
+        positional_dropout_rate: 0.1
+        attention_dropout_rate: 0
+        normalize_before: True
+        input_layer: 'linear'
+        pos_enc_layer_type: 'rel_pos_espnet'
+        selfattention_layer_type: 'rel_selfattn'
+        use_cnn_module: False
+        macaron_style: False
+        use_dynamic_chunk: False
+        use_dynamic_left_chunk: False
+        static_chunk_size: 1
+    llm: !new:cosyvoice.transformer.encoder.TransformerEncoder
+        input_size: !ref <llm_input_size>
+        output_size: !ref <llm_output_size>
+        attention_heads: 8
+        linear_units: 2048
+        num_blocks: 7
+        dropout_rate: 0.1
+        positional_dropout_rate: 0.1
+        attention_dropout_rate: 0
+        input_layer: 'linear_legacy'
+        pos_enc_layer_type: 'rel_pos_espnet'
+        selfattention_layer_type: 'rel_selfattn'
+        static_chunk_size: 1
+
+flow: !new:cosyvoice.flow.flow.MaskedDiffWithXvec
+    input_size: 512
+    output_size: 80
+    spk_embed_dim: !ref <spk_embed_dim>
+    output_type: 'mel'
+    vocab_size: 8192
+    input_frame_rate: 25
+    only_mask_loss: True
+    encoder: !new:cosyvoice.transformer.encoder.BlockConformerEncoder
+        output_size: 512
+        attention_heads: 8
+        linear_units: 2048
+        num_blocks: 6
+        dropout_rate: 0.1
+        positional_dropout_rate: 0.1
+        attention_dropout_rate: 0.1
+        normalize_before: True
+        input_layer: 'linear'
+        pos_enc_layer_type: 'rel_pos_espnet'
+        selfattention_layer_type: 'block_rel_selfattn'
+        block_size: 10
+        input_size: 512
+        use_cnn_module: False
+        macaron_style: False
+    length_regulator: !new:cosyvoice.flow.length_regulator.InterpolateRegulator
+        channels: 80
+        sampling_ratios: [1, 1, 1, 1]
+    decoder: !new:cosyvoice.flow.flow_matching.ConditionalCFM
+        in_channels: 240
+        n_spks: 1
+        spk_emb_dim: 80
+        cfm_params: !new:omegaconf.DictConfig
+            content:
+                sigma_min: 1e-06
+                solver: 'euler'
+                t_scheduler: 'cosine'
+                training_cfg_rate: 0.2
+                inference_cfg_rate: 0.7
+                reg_loss_type: 'l1'
+        estimator: !new:cosyvoice.flow.decoder.ConditionalDecoder
+            in_channels: 320
+            out_channels: 80
+            channels: [256, 256]
+            dropout: 0
+            attention_head_dim: 64
+            n_blocks: 4
+            num_mid_blocks: 12
+            num_heads: 8
+            act_fn: 'gelu'
+
+hift: !new:cosyvoice.hifigan.generator.HiFTGenerator
+    in_channels: 80
+    base_channels: 512
+    nb_harmonics: 8
+    sampling_rate: !ref <sample_rate>
+    nsf_alpha: 0.1
+    nsf_sigma: 0.003
+    nsf_voiced_threshold: 10
+    upsample_rates: [8, 8]
+    upsample_kernel_sizes: [16, 16]
+    istft_params:
+        n_fft: 16
+        hop_len: 4
+    resblock_kernel_sizes: [3, 7, 11]
+    resblock_dilation_sizes: [[1, 3, 5], [1, 3, 5], [1, 3, 5]]
+    source_resblock_kernel_sizes: [7, 11]
+    source_resblock_dilation_sizes: [[1, 3, 5], [1, 3, 5]]
+    lrelu_slope: 0.1
+    audio_limit: 0.99
+    f0_predictor: !new:cosyvoice.hifigan.f0_predictor.ConvRNNF0Predictor
+        num_class: 1
+        in_channels: 80
+        cond_channels: 512

decoder/flow.pt

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+oid sha256:28655ded7fce95b338ad22b7967ebc28fdb6a13ff4c42a4032dbfff6c9c12187
+size 428400959

decoder/hift.pt

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+size 81897015

tokenizer/config.json

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+{
+  "_name_or_path": "openai/whisper-large-v3",
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperLFQEncoder"
+  ],
+  "attention_dropout": 0.0,
+  "batch_maximization_weight": 0.3,
+  "classifier_proj_size": 256,
+  "d_model": 1280,
+  "delta_cross_logdet_reg_loss": 1.0,
+  "dropout": 0.0,
+  "enable_noise_contrastive": false,
+  "encoder_attention_heads": 20,
+  "encoder_causal_attention": false,
+  "encoder_causal_convolution": false,
+  "encoder_ffn_dim": 5120,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 32,
+  "fix_noise_commit_loss_ratio": false,
+  "init_std": 0.06,
+  "is_encoder_decoder": true,
+  "lambda_consensus_loss_ratio": 0.25,
+  "layernorm_after_quantize": true,
+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.05,
+  "max_length": 448,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
+  "noise_commit_loss_ratio": 0.3333333333333333,
+  "num_clean_input": 3,
+  "num_hidden_layers": 32,
+  "num_mel_bins": 128,
+  "num_voters": 5,
+  "pooling_kernel_size": 2,
+  "pooling_position": 16,
+  "pooling_type": "avg",
+  "quantize_commit_coefficient": 0.25,
+  "quantize_encoder_only": true,
+  "quantize_position": 16,
+  "quantize_vocab_size": 8192,
+  "sample_minimization_weight": 0.1,
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.0",
+  "use_aggregated_entropy": true,
+  "use_cache": true,
+  "use_codebook_ce_loss": true,
+  "use_commit_loss": true,
+  "use_projection_bias": false,
+  "use_svlfq": true,
+  "use_weighted_layer_sum": false
+}

tokenizer/model.safetensors

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+size 1296837992

tokenizer/preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 128,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}