Text-to-Speech
Transformers
Safetensors
English
emosphere_pp
feature-extraction
emotional-tts
zero-shot-tts
flow-matching
emosphere
custom_code
Instructions to use RetentionLabs/EmoSphere-PP-16kHz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RetentionLabs/EmoSphere-PP-16kHz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="RetentionLabs/EmoSphere-PP-16kHz", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RetentionLabs/EmoSphere-PP-16kHz", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,709 Bytes
2f05e3a 39f692e 4be7049 2f05e3a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 | {
"processor_class": "EmoSpherePPProcessor",
"phone_set": [
"!",
",",
".",
":",
"<BOS>",
"<EOS>",
"?",
"AA1",
"AA2",
"AE1",
"AE2",
"AH0",
"AH1",
"AH2",
"AO0",
"AO1",
"AO2",
"AW0",
"AW1",
"AW2",
"AY0",
"AY1",
"AY2",
"B",
"CH",
"D",
"DH",
"EH0",
"EH1",
"EH2",
"ER0",
"ER1",
"EY0",
"EY1",
"EY2",
"F",
"G",
"HH",
"IH0",
"IH1",
"IH2",
"IY0",
"IY1",
"IY2",
"JH",
"K",
"L",
"M",
"N",
"NG",
"OW0",
"OW1",
"OW2",
"OY1",
"OY2",
"P",
"R",
"S",
"SH",
"T",
"TH",
"UH1",
"UH2",
"UW0",
"UW1",
"UW2",
"V",
"W",
"Y",
"Z",
"ZH",
"|"
],
"vad_quartiles": {
"neutral": [
0.08786924783163853,
0.18281635027250842
],
"angry": [
0.29262144907347293,
0.4512920748760003
],
"happy": [
0.23541007374705025,
0.4061585055276832
],
"sad": [
0.1747908845908132,
0.3456464010802644
],
"surprise": [
0.29179362126658487,
0.4534077316138918
]
},
"vad_centers": {
"neutral": [
0.4135,
0.5169,
0.362
],
"angry": [
0.37068613,
0.4814421,
0.37709341
],
"happy": [
0.36792182,
0.48303542,
0.34562907
],
"sad": [
0.48519272,
0.57727589,
0.39524114
],
"surprise": [
0.36877737,
0.48431942,
0.36644742
]
},
"auto_map": {
"AutoProcessor": "processing_emosphere_pp.EmoSpherePPProcessor"
},
"dtype": "float32"
}
|