| # Voices | |
| - 🇺🇸 [American English](#american-english): 11F 9M | |
| - 🇬🇧 [British English](#british-english): 4F 4M | |
| - 🇯🇵 [Japanese](#japanese): 4F 1M | |
| - 🇨🇳 [Mandarin Chinese](#mandarin-chinese): 4F 4M | |
| - 🇪🇸 [Spanish](#spanish): 1F 2M | |
| - 🇫🇷 [French](#french): 1F | |
| - 🇮🇳 [Hindi](#hindi): 2F 2M | |
| - 🇮🇹 [Italian](#italian): 1F 1M | |
| - 🇧🇷 [Brazilian Portuguese](#brazilian-portuguese): 1F 2M | |
| 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. | |
| Subjectively, voices will sound better or worse to different people. | |
| Support for non-English languages may be absent or thin due to weak G2P and/or lack of training data. Some languages are only represented by a small handful or even just one voice (French). | |
| Most voices perform best on a "goldilocks range" of 100-200 tokens out of ~500 possible. Voices may perform worse at the extremes: | |
| - **Weakness** on short utterances, especially less than 10-20 tokens. Root cause could be lack of short-utterance training data and/or model architecture. One possible inference mitigation is to bundle shorter utterances together. | |
| - **Rushing** on long utterances, especially over 400 tokens. You can chunk down to shorter utterances or adjust the `speed` parameter to mitigate this. | |
| **Target Quality** | |
| - How high quality is the reference voice? This grade may be impacted by audio quality, artifacts, compression, & sample rate. | |
| - How well do the text labels match the audio? Text/audio misalignment (e.g. from hallucinations) will lower this grade. | |
| **Training Duration** | |
| - How much audio was seen during training? Smaller durations result in a lower overall grade. | |
| - 10 hours <= **HH hours** < 100 hours | |
| - 1 hour <= H hours < 10 hours | |
| - 10 minutes <= MM minutes < 100 minutes | |
| - 1 minute <= _M minutes_ 🤏 < 10 minutes | |
| ### American English | |
| - `lang_code='a'` in [`misaki[en]`](https://github.com/hexgrad/misaki) | |
| - espeak-ng `en-us` fallback | |
| | Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | | |
| | ---- | ------ | -------------- | ----------------- | ------------- | ------ | | |
| | **af\_heart** | 🚺❤️ | | | **A** | `0ab5709b` | | |
| | af_alloy | 🚺 | B | MM minutes | C | `6d877149` | | |
| | af_aoede | 🚺 | B | H hours | C+ | `c03bd1a4` | | |
| | af_bella | 🚺🔥 | **A** | **HH hours** | **A-** | `8cb64e02` | | |
| | af_jessica | 🚺 | C | MM minutes | D | `cdfdccb8` | | |
| | af_kore | 🚺 | B | H hours | C+ | `8bfbc512` | | |
| | af_nicole | 🚺🎧 | B | **HH hours** | B- | `c5561808` | | |
| | af_nova | 🚺 | B | MM minutes | C | `e0233676` | | |
| | af_river | 🚺 | C | MM minutes | D | `e149459b` | | |
| | af_sarah | 🚺 | B | H hours | C+ | `49bd364e` | | |
| | af_sky | 🚺 | B | _M minutes_ 🤏 | C- | `c799548a` | | |
| | am_adam | 🚹 | D | H hours | F+ | `ced7e284` | | |
| | am_echo | 🚹 | C | MM minutes | D | `8bcfdc85` | | |
| | am_eric | 🚹 | C | MM minutes | D | `ada66f0e` | | |
| | am_fenrir | 🚹 | B | H hours | C+ | `98e507ec` | | |
| | am_liam | 🚹 | C | MM minutes | D | `c8255075` | | |
| | am_michael | 🚹 | B | H hours | C+ | `9a443b79` | | |
| | am_onyx | 🚹 | C | MM minutes | D | `e8452be1` | | |
| | am_puck | 🚹 | B | H hours | C+ | `dd1d8973` | | |
| | am_santa | 🚹 | C | _M minutes_ 🤏 | D- | `7f2f7582` | | |
| ### British English | |
| - `lang_code='b'` in [`misaki[en]`](https://github.com/hexgrad/misaki) | |
| - espeak-ng `en-gb` fallback | |
| | Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | | |
| | ---- | ------ | -------------- | ----------------- | ------------- | ------ | | |
| | bf_alice | 🚺 | C | MM minutes | D | `d292651b` | | |
| | bf_emma | 🚺 | B | **HH hours** | B- | `d0a423de` | | |
| | bf_isabella | 🚺 | B | MM minutes | C | `cdd4c370` | | |
| | bf_lily | 🚺 | C | MM minutes | D | `6e09c2e4` | | |
| | bm_daniel | 🚹 | C | MM minutes | D | `fc3fce4e` | | |
| | bm_fable | 🚹 | B | MM minutes | C | `d44935f3` | | |
| | bm_george | 🚹 | B | MM minutes | C | `f1bc8122` | | |
| | bm_lewis | 🚹 | C | H hours | D+ | `b5204750` | | |
| ### Japanese | |
| - `lang_code='j'` in [`misaki[ja]`](https://github.com/hexgrad/misaki) | |
| - Total Japanese training data: H hours | |
| | Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | CC BY | | |
| | ---- | ------ | -------------- | ----------------- | ------------- | ------ | ----- | | |
| | jf_alpha | 🚺 | B | H hours | C+ | `1bf4c9dc` | | | |
| | jf_gongitsune | 🚺 | B | MM minutes | C | `1b171917` | [gongitsune](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__gongitsune.txt) | | |
| | jf_nezumi | 🚺 | B | _M minutes_ 🤏 | C- | `d83f007a` | [nezuminoyomeiri](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__nezuminoyomeiri.txt) | | |
| | jf_tebukuro | 🚺 | B | MM minutes | C | `0d691790` | [tebukurowokaini](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__tebukurowokaini.txt) | | |
| | jm_kumo | 🚹 | B | _M minutes_ 🤏 | C- | `98340afd` | [kumonoito](https://github.com/koniwa/koniwa/blob/master/source/tnc/tnc__kumonoito.txt) | | |
| ### Mandarin Chinese | |
| - `lang_code='z'` in [`misaki[zh]`](https://github.com/hexgrad/misaki) | |
| - Total Mandarin Chinese training data: H hours | |
| | Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | | |
| | ---- | ------ | -------------- | ----------------- | ------------- | ------ | | |
| | zf_xiaobei | 🚺 | C | MM minutes | D | `9b76be63` | | |
| | zf_xiaoni | 🚺 | C | MM minutes | D | `95b49f16` | | |
| | zf_xiaoxiao | 🚺 | C | MM minutes | D | `cfaf6f2d` | | |
| | zf_xiaoyi | 🚺 | C | MM minutes | D | `b5235dba` | | |
| | zm_yunjian | 🚹 | C | MM minutes | D | `76cbf8ba` | | |
| | zm_yunxi | 🚹 | C | MM minutes | D | `dbe6e1ce` | | |
| | zm_yunxia | 🚹 | C | MM minutes | D | `bb2b03b0` | | |
| | zm_yunyang | 🚹 | C | MM minutes | D | `5238ac22` | | |
| ### Spanish | |
| - `lang_code='e'` in [`misaki[en]`](https://github.com/hexgrad/misaki) | |
| - espeak-ng `es` | |
| | Name | Traits | SHA256 | | |
| | ---- | ------ | ------ | | |
| | ef_dora | 🚺 | `d9d69b0f` | | |
| | em_alex | 🚹 | `5eac53f7` | | |
| | em_santa | 🚹 | `aa8620cb` | | |
| ### French | |
| - `lang_code='f'` in [`misaki[en]`](https://github.com/hexgrad/misaki) | |
| - espeak-ng `fr-fr` | |
| - Total French training data: <11 hours | |
| | Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | CC BY | | |
| | ---- | ------ | -------------- | ----------------- | ------------- | ------ | ----- | | |
| | ff_siwis | 🚺 | B | <11 hours | B- | `8073bf2d` | [SIWIS](https://datashare.ed.ac.uk/handle/10283/2353) | | |
| ### Hindi | |
| - `lang_code='h'` in [`misaki[en]`](https://github.com/hexgrad/misaki) | |
| - espeak-ng `hi` | |
| - Total Hindi training data: H hours | |
| | Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | | |
| | ---- | ------ | -------------- | ----------------- | ------------- | ------ | | |
| | hf_alpha | 🚺 | B | MM minutes | C | `06906fe0` | | |
| | hf_beta | 🚺 | B | MM minutes | C | `63c0a1a6` | | |
| | hm_omega | 🚹 | B | MM minutes | C | `b55f02a8` | | |
| | hm_psi | 🚹 | B | MM minutes | C | `2f0f055c` | | |
| ### Italian | |
| - `lang_code='i'` in [`misaki[en]`](https://github.com/hexgrad/misaki) | |
| - espeak-ng `it` | |
| - Total Italian training data: H hours | |
| | Name | Traits | Target Quality | Training Duration | Overall Grade | SHA256 | | |
| | ---- | ------ | -------------- | ----------------- | ------------- | ------ | | |
| | if_sara | 🚺 | B | MM minutes | C | `6c0b253b` | | |
| | im_nicola | 🚹 | B | MM minutes | C | `234ed066` | | |
| ### Brazilian Portuguese | |
| - `lang_code='p'` in [`misaki[en]`](https://github.com/hexgrad/misaki) | |
| - espeak-ng `pt-br` | |
| | Name | Traits | SHA256 | | |
| | ---- | ------ | ------ | | |
| | pf_dora | 🚺 | `07e4ff98` | | |
| | pm_alex | 🚹 | `cf0ba8c5` | | |
| | pm_santa | 🚹 | `d4210316` | | |