Datasets:
Tasks:
Text-to-Speech
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
kokoro-82M
License:
voices
stringlengths 2
11
| tensor
sequencelengths 511
511
|
---|---|
af | [[[-0.2652127146720886,0.1360752433538437,-0.04390159249305725,-0.02971639297902584,-0.1134719550609(...TRUNCATED) |
af_bella | [[[-0.18230007588863373,0.13846321403980255,-0.0694742500782013,0.04682711139321327,-0.1308719366788(...TRUNCATED) |
af_nicole | [[[-0.02709878422319889,0.027324803173542023,-0.23722366988658905,-0.28041407465934753,-0.5189462304(...TRUNCATED) |
af_sarah | [[[-0.3481253683567047,0.13368727266788483,-0.018328938633203506,-0.10625989735126495,-0.09607198089(...TRUNCATED) |
af_sky | [[[-0.3382578492164612,-0.09134633839130402,0.14364251494407654,-0.2724664509296417,-0.1220948323607(...TRUNCATED) |
am_adam | [[[-0.06618323177099228,0.1601543426513672,-0.08515165001153946,0.15565742552280426,-0.2935728728771(...TRUNCATED) |
am_michael | [[[-0.1796865016222,0.1411287933588028,-0.05157635733485222,-0.1529253125190735,-0.245713010430336,-(...TRUNCATED) |
bf_emma | [[[-0.16838793456554413,0.14083364605903625,-0.08112974464893341,-0.006938330363482237,-0.0072707999(...TRUNCATED) |
bf_isabella | [[[-0.0945773497223854,-0.02385879121720791,-0.13582783937454224,-0.1491769552230835,-0.075081706047(...TRUNCATED) |
bm_george | [[[-0.23411038517951965,-0.030513668432831764,-0.3705330789089203,0.43368762731552124,-0.15910805761(...TRUNCATED) |
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Kokoro-82M Voices
This dataset contains all the voices available in hexgrad/Kokoro-82M. This dataset provides the voices in 3 different formats.
- Individual voices embeddings in different JSON file
- Single JSON which contains all the voices in a JSON object.
- Parquet format for usage via
datasets
The voices name is the same as the.pth
file names shown below.
voices = [
"af",
"af_bella",
"af_nicole",
"af_sarah",
"af_sky",
"am_adam",
"am_michael",
"bf_emma",
"bf_isabella",
"bm_george",
"bm_lewis",
]
For example, the "af" voices embeddings can be obtained using the "af.json" file which contains the embeddings as a JSON array.
The same "af" voices can be obtain in the single file by accessing the "af" name in the JSON object.
See Usage
for more information on how to retreive the embeddings.
Usage
Some example usage of downloading the "af" voice embedding.
Downloading the JSON All
# pip install -U -q huggingface_hub numpy
import json
import numpy as np
from huggingface_hub import hf_hub_download
file = hf_hub_download(
repo_id="ecyht2/kokoro-82M-voices",
repo_type="dataset",
filename="voices.json"
)
with open(file, "r", encoding="utf-8") as f:
voices = json.load(f)
voice = np.array(voices.get("af")) # Change "af" to the voice that you want
print(voice.shape)
# (511, 1, 256)
Downloading the JSON Single
# pip install -U -q huggingface_hub numpy
import json
import numpy as np
from huggingface_hub import hf_hub_download
file = hf_hub_download(
repo_id="ecyht2/kokoro-82M-voices",
repo_type="dataset",
filename="af.json" # Change "af" to the voice that you want
)
with open(file, "r", encoding="utf-8") as f:
voice = json.load(f)
voice = np.array(voice)
print(voice.shape)
# (511, 1, 256)
Using Huggingface Datasets
# pip install -U -q datasets numpy
from datasets import load_dataset
ds = load_dataset(repo, split="train")
for i in ds:
if i["voices"] == "af":
voice = np.array(i["tensor"])
break
print(voice.shape)
# (511, 1, 256)
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