Upload 2 files
Browse files
README.md
CHANGED
@@ -24,7 +24,7 @@ pipeline_tag: text-to-speech
|
|
24 |
|
25 |
| Model | Published | Training Data | Compute (A100 80GB) | Langs & Voices | SHA256 |
|
26 |
| ----- | --------- | ------------- | ------------------- | -------------- | ------ |
|
27 |
-
| **v1.0** | **2025 Jan 27** | **Few hundred hrs** | **$1000 for 1000 hrs** | [**
|
28 |
| [v0.19](https://huggingface.co/hexgrad/kLegacy/tree/main/v0.19) | 2024 Dec 25 | <100 hrs | $400 for 500 hrs | 1 & 10 | `3b0c392f` |
|
29 |
|
30 |
### Usage
|
@@ -37,9 +37,11 @@ You can run this cell on [Google Colab](https://colab.research.google.com/).
|
|
37 |
!pip install -q kokoro>=0.3.1 soundfile
|
38 |
# 2️⃣ Install espeak, used for English OOD fallback and some non-English languages
|
39 |
!apt-get -qq -y install espeak-ng > /dev/null 2>&1
|
|
|
40 |
# 🇫🇷 'f' => French fr-fr
|
41 |
# 🇮🇳 'h' => Hindi hi
|
42 |
# 🇮🇹 'i' => Italian it
|
|
|
43 |
|
44 |
# 3️⃣ Initalize a pipeline
|
45 |
from kokoro import KPipeline
|
@@ -60,9 +62,11 @@ These were to have an enormous impact, not only because they were associated wit
|
|
60 |
'''
|
61 |
# text = '「もしおれがただ偶然、そしてこうしようというつもりでなくここに立っているのなら、ちょっとばかり絶望するところだな」と、そんなことが彼の頭に思い浮かんだ。'
|
62 |
# text = '中國人民不信邪也不怕邪,不惹事也不怕事,任何外國不要指望我們會拿自己的核心利益做交易,不要指望我們會吞下損害我國主權、安全、發展利益的苦果!'
|
|
|
63 |
# text = 'Le dromadaire resplendissant déambulait tranquillement dans les méandres en mastiquant de petites feuilles vernissées.'
|
64 |
# text = 'ट्रांसपोर्टरों की हड़ताल लगातार पांचवें दिन जारी, दिसंबर से इलेक्ट्रॉनिक टोल कलेक्शनल सिस्टम'
|
65 |
# text = "Allora cominciava l'insonnia, o un dormiveglia peggiore dell'insonnia, che talvolta assumeva i caratteri dell'incubo."
|
|
|
66 |
|
67 |
# 4️⃣ Generate, display, and save audio files in a loop.
|
68 |
generator = pipeline(
|
|
|
24 |
|
25 |
| Model | Published | Training Data | Compute (A100 80GB) | Langs & Voices | SHA256 |
|
26 |
| ----- | --------- | ------------- | ------------------- | -------------- | ------ |
|
27 |
+
| **v1.0** | **2025 Jan 27** | **Few hundred hrs** | **$1000 for 1000 hrs** | [**8 & 53**](https://huggingface.co/hexgrad/Kokoro-82M/blob/main/VOICES.md) | `496dba11` |
|
28 |
| [v0.19](https://huggingface.co/hexgrad/kLegacy/tree/main/v0.19) | 2024 Dec 25 | <100 hrs | $400 for 500 hrs | 1 & 10 | `3b0c392f` |
|
29 |
|
30 |
### Usage
|
|
|
37 |
!pip install -q kokoro>=0.3.1 soundfile
|
38 |
# 2️⃣ Install espeak, used for English OOD fallback and some non-English languages
|
39 |
!apt-get -qq -y install espeak-ng > /dev/null 2>&1
|
40 |
+
# 🇪🇸 'e' => Spanish es
|
41 |
# 🇫🇷 'f' => French fr-fr
|
42 |
# 🇮🇳 'h' => Hindi hi
|
43 |
# 🇮🇹 'i' => Italian it
|
44 |
+
# 🇧🇷 'p' => Brazilian Portuguese pt-br
|
45 |
|
46 |
# 3️⃣ Initalize a pipeline
|
47 |
from kokoro import KPipeline
|
|
|
62 |
'''
|
63 |
# text = '「もしおれがただ偶然、そしてこうしようというつもりでなくここに立っているのなら、ちょっとばかり絶望するところだな」と、そんなことが彼の頭に思い浮かんだ。'
|
64 |
# text = '中國人民不信邪也不怕邪,不惹事也不怕事,任何外國不要指望我們會拿自己的核心利益做交易,不要指望我們會吞下損害我國主權、安全、發展利益的苦果!'
|
65 |
+
# text = 'Los partidos políticos tradicionales compiten con los populismos y los movimientos asamblearios.'
|
66 |
# text = 'Le dromadaire resplendissant déambulait tranquillement dans les méandres en mastiquant de petites feuilles vernissées.'
|
67 |
# text = 'ट्रांसपोर्टरों की हड़ताल लगातार पांचवें दिन जारी, दिसंबर से इलेक्ट्रॉनिक टोल कलेक्शनल सिस्टम'
|
68 |
# text = "Allora cominciava l'insonnia, o un dormiveglia peggiore dell'insonnia, che talvolta assumeva i caratteri dell'incubo."
|
69 |
+
# text = 'Elabora relatórios de acompanhamento cronológico para as diferentes unidades do Departamento que propõem contratos.'
|
70 |
|
71 |
# 4️⃣ Generate, display, and save audio files in a loop.
|
72 |
generator = pipeline(
|
VOICES.md
CHANGED
@@ -2,11 +2,13 @@
|
|
2 |
|
3 |
- 🇺🇸 [American English](#american-english): 10F 9M
|
4 |
- 🇬🇧 [British English](#british-english): 4F 4M
|
|
|
|
|
|
|
5 |
- 🇫🇷 [French](#french): 1F
|
6 |
- 🇮🇳 [Hindi](#hindi): 2F 2M
|
7 |
- 🇮🇹 [Italian](#italian): 1F 1M
|
8 |
-
-
|
9 |
-
- 🇨🇳 [Mandarin Chinese](#mandarin-chinese): 4F 4M
|
10 |
|
11 |
For each voice, the given grades are intended to be estimates of the **quality and quantity** of its associated training data, both of which impact overall inference quality.
|
12 |
|
@@ -27,7 +29,7 @@ Most voices perform best on a "goldilocks range" of 100-200 tokens out of ~500 p
|
|
27 |
- 10 hours <= **HH hours** < 100 hours
|
28 |
- 1 hour <= H hours < 10 hours
|
29 |
- 10 minutes <= MM minutes < 100 minutes
|
30 |
-
- 1 minute <= _M minutes_ < 10 minutes
|
31 |
|
32 |
### American English
|
33 |
|
@@ -45,7 +47,7 @@ Most voices perform best on a "goldilocks range" of 100-200 tokens out of ~500 p
|
|
45 |
| af_nova | 🚺 | B | MM minutes | C | `e0233676` |
|
46 |
| af_river | 🚺 | C | MM minutes | D | `e149459b` |
|
47 |
| af_sarah | 🚺 | B | H hours | C+ | `49bd364e` |
|
48 |
-
| af_sky |
|
49 |
| am_adam | 🚹 | D | H hours | F+ | `ced7e284` |
|
50 |
| am_echo | 🚹 | C | MM minutes | D | `8bcfdc85` |
|
51 |
| am_eric | 🚹 | C | MM minutes | D | `ada66f0e` |
|
@@ -54,7 +56,7 @@ Most voices perform best on a "goldilocks range" of 100-200 tokens out of ~500 p
|
|
54 |
| am_michael | 🚹 | B | H hours | C+ | `9a443b79` |
|
55 |
| am_onyx | 🚹 | C | MM minutes | D | `e8452be1` |
|
56 |
| am_puck | 🚹 | B | H hours | C+ | `dd1d8973` |
|
57 |
-
| am_santa |
|
58 |
|
59 |
### British English
|
60 |
|
@@ -72,6 +74,46 @@ Most voices perform best on a "goldilocks range" of 100-200 tokens out of ~500 p
|
|
72 |
| bm_george | 🚹 | B | MM minutes | C | `f1bc8122` |
|
73 |
| bm_lewis | 🚹 | C | H hours | D+ | `b5204750` |
|
74 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
75 |
### French
|
76 |
|
77 |
- `lang_code='f'` in [`misaki[en]`](https://github.com/hexgrad/misaki)
|
@@ -106,31 +148,13 @@ Most voices perform best on a "goldilocks range" of 100-200 tokens out of ~500 p
|
|
106 |
| if_sara | 🚺 | B | MM minutes | C | `6c0b253b` |
|
107 |
| im_nicola | 🚹 | B | MM minutes | C | `234ed066` |
|
108 |
|
109 |
-
###
|
110 |
|
111 |
-
- `lang_code='
|
112 |
-
-
|
113 |
|
114 |
-
| Name | Traits |
|
115 |
-
| ---- | ------ |
|
116 |
-
|
|
117 |
-
|
|
118 |
-
|
|
119 |
-
| jf_tebukuro | 🚺 | B | MM minutes | C | `0d691790` | [tebukurowokaini](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__tebukurowokaini.txt) |
|
120 |
-
| jm_kumo | 🚹🤏 | B | _M minutes_ | C- | `98340afd` | [kumonoito](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__kumonoito.txt) |
|
121 |
-
|
122 |
-
### Mandarin Chinese
|
123 |
-
|
124 |
-
- `lang_code='z'` in [`misaki[zh]`](https://github.com/hexgrad/misaki)
|
125 |
-
- Total Mandarin Chinese training data: H hours
|
126 |
-
|
127 |
-
| Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 |
|
128 |
-
| ---- | ------ | -------------- | ----------------- | ------------- | ------ |
|
129 |
-
| zf_xiaobei | 🚺 | C | MM minutes | D | `9b76be63` |
|
130 |
-
| zf_xiaoni | 🚺 | C | MM minutes | D | `95b49f16` |
|
131 |
-
| zf_xiaoxiao | 🚺 | C | MM minutes | D | `cfaf6f2d` |
|
132 |
-
| zf_xiaoyi | 🚺 | C | MM minutes | D | `b5235dba` |
|
133 |
-
| zm_yunjian | 🚹 | C | MM minutes | D | `76cbf8ba` |
|
134 |
-
| zm_yunxi | 🚹 | C | MM minutes | D | `dbe6e1ce` |
|
135 |
-
| zm_yunxia | 🚹 | C | MM minutes | D | `bb2b03b0` |
|
136 |
-
| zm_yunyang | 🚹 | C | MM minutes | D | `5238ac22` |
|
|
|
2 |
|
3 |
- 🇺🇸 [American English](#american-english): 10F 9M
|
4 |
- 🇬🇧 [British English](#british-english): 4F 4M
|
5 |
+
- 🇯🇵 [Japanese](#japanese): 4F 1M
|
6 |
+
- 🇨🇳 [Mandarin Chinese](#mandarin-chinese): 4F 4M
|
7 |
+
- 🇪🇸 [Spanish](#spanish): 1F 2M
|
8 |
- 🇫🇷 [French](#french): 1F
|
9 |
- 🇮🇳 [Hindi](#hindi): 2F 2M
|
10 |
- 🇮🇹 [Italian](#italian): 1F 1M
|
11 |
+
- 🇧🇷 [Brazilian Portuguese](#brazilian-portuguese): 1F 2M
|
|
|
12 |
|
13 |
For each voice, the given grades are intended to be estimates of the **quality and quantity** of its associated training data, both of which impact overall inference quality.
|
14 |
|
|
|
29 |
- 10 hours <= **HH hours** < 100 hours
|
30 |
- 1 hour <= H hours < 10 hours
|
31 |
- 10 minutes <= MM minutes < 100 minutes
|
32 |
+
- 1 minute <= _M minutes_ 🤏 < 10 minutes
|
33 |
|
34 |
### American English
|
35 |
|
|
|
47 |
| af_nova | 🚺 | B | MM minutes | C | `e0233676` |
|
48 |
| af_river | 🚺 | C | MM minutes | D | `e149459b` |
|
49 |
| af_sarah | 🚺 | B | H hours | C+ | `49bd364e` |
|
50 |
+
| af_sky | 🚺 | B | _M minutes_ 🤏 | C- | `c799548a` |
|
51 |
| am_adam | 🚹 | D | H hours | F+ | `ced7e284` |
|
52 |
| am_echo | 🚹 | C | MM minutes | D | `8bcfdc85` |
|
53 |
| am_eric | 🚹 | C | MM minutes | D | `ada66f0e` |
|
|
|
56 |
| am_michael | 🚹 | B | H hours | C+ | `9a443b79` |
|
57 |
| am_onyx | 🚹 | C | MM minutes | D | `e8452be1` |
|
58 |
| am_puck | 🚹 | B | H hours | C+ | `dd1d8973` |
|
59 |
+
| am_santa | 🚹 | C | _M minutes_ 🤏 | D- | `7f2f7582` |
|
60 |
|
61 |
### British English
|
62 |
|
|
|
74 |
| bm_george | 🚹 | B | MM minutes | C | `f1bc8122` |
|
75 |
| bm_lewis | 🚹 | C | H hours | D+ | `b5204750` |
|
76 |
|
77 |
+
### Japanese
|
78 |
+
|
79 |
+
- `lang_code='j'` in [`misaki[ja]`](https://github.com/hexgrad/misaki)
|
80 |
+
- Total Japanese training data: H hours
|
81 |
+
|
82 |
+
| Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | CC BY |
|
83 |
+
| ---- | ------ | -------------- | ----------------- | ------------- | ------ | ----- |
|
84 |
+
| jf_alpha | 🚺 | B | H hours | C+ | `1bf4c9dc` | |
|
85 |
+
| jf_gongitsune | 🚺 | B | MM minutes | C | `1b171917` | [gongitsune](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__gongitsune.txt) |
|
86 |
+
| jf_nezumi | 🚺 | B | _M minutes_ 🤏 | C- | `d83f007a` | [nezuminoyomeiri](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__nezuminoyomeiri.txt) |
|
87 |
+
| jf_tebukuro | 🚺 | B | MM minutes | C | `0d691790` | [tebukurowokaini](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__tebukurowokaini.txt) |
|
88 |
+
| jm_kumo | 🚹 | B | _M minutes_ 🤏 | C- | `98340afd` | [kumonoito](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__kumonoito.txt) |
|
89 |
+
|
90 |
+
### Mandarin Chinese
|
91 |
+
|
92 |
+
- `lang_code='z'` in [`misaki[zh]`](https://github.com/hexgrad/misaki)
|
93 |
+
- Total Mandarin Chinese training data: H hours
|
94 |
+
|
95 |
+
| Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 |
|
96 |
+
| ---- | ------ | -------------- | ----------------- | ------------- | ------ |
|
97 |
+
| zf_xiaobei | 🚺 | C | MM minutes | D | `9b76be63` |
|
98 |
+
| zf_xiaoni | 🚺 | C | MM minutes | D | `95b49f16` |
|
99 |
+
| zf_xiaoxiao | 🚺 | C | MM minutes | D | `cfaf6f2d` |
|
100 |
+
| zf_xiaoyi | 🚺 | C | MM minutes | D | `b5235dba` |
|
101 |
+
| zm_yunjian | 🚹 | C | MM minutes | D | `76cbf8ba` |
|
102 |
+
| zm_yunxi | 🚹 | C | MM minutes | D | `dbe6e1ce` |
|
103 |
+
| zm_yunxia | 🚹 | C | MM minutes | D | `bb2b03b0` |
|
104 |
+
| zm_yunyang | 🚹 | C | MM minutes | D | `5238ac22` |
|
105 |
+
|
106 |
+
### Spanish
|
107 |
+
|
108 |
+
- `lang_code='e'` in [`misaki[en]`](https://github.com/hexgrad/misaki)
|
109 |
+
- espeak-ng `es`
|
110 |
+
|
111 |
+
| Name | Traits | SHA256 |
|
112 |
+
| ---- | ------ | ------ |
|
113 |
+
| ef_dora | 🚺 | `d9d69b0f` |
|
114 |
+
| em_alex | 🚹 | `5eac53f7` |
|
115 |
+
| em_santa | 🚹 | `aa8620cb` |
|
116 |
+
|
117 |
### French
|
118 |
|
119 |
- `lang_code='f'` in [`misaki[en]`](https://github.com/hexgrad/misaki)
|
|
|
148 |
| if_sara | 🚺 | B | MM minutes | C | `6c0b253b` |
|
149 |
| im_nicola | 🚹 | B | MM minutes | C | `234ed066` |
|
150 |
|
151 |
+
### Brazilian Portuguese
|
152 |
|
153 |
+
- `lang_code='p'` in [`misaki[en]`](https://github.com/hexgrad/misaki)
|
154 |
+
- espeak-ng `pt-br`
|
155 |
|
156 |
+
| Name | Traits | SHA256 |
|
157 |
+
| ---- | ------ | ------ |
|
158 |
+
| pf_dora | 🚺 | `07e4ff98` |
|
159 |
+
| pm_alex | 🚹 | `cf0ba8c5` |
|
160 |
+
| pm_santa | 🚹 | `d4210316` |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|