#!/usr/bin/env python3 import argparse from dataclasses import dataclass from typing import List, Optional import jinja2 # pip install iso639-lang from iso639 import Lang def get_args(): parser = argparse.ArgumentParser() parser.add_argument( "--total", type=int, default=1, help="Number of runners", ) parser.add_argument( "--index", type=int, default=0, help="Index of the current runner", ) return parser.parse_args() @dataclass class TtsModel: model_dir: str model_name: str = "" # for vits acoustic_model_name: str = "" # for matcha vocoder: str = "" # for matcha voices: str = "" # for kokoro lang: str = "" # en, zh, fr, de, etc. lang2: str = "" # en, zh, fr, de, etc. rule_fsts: Optional[List[str]] = None rule_fars: Optional[List[str]] = None data_dir: Optional[str] = None dict_dir: Optional[str] = None is_char: bool = False lang_iso_639_3: str = "" lang_iso_639_3_2: str = "" lexicon: str = "" def convert_lang_to_iso_639_3(models: List[TtsModel]): for m in models: if m.lang_iso_639_3 == "": m.lang_iso_639_3 = Lang(m.lang).pt3 if m.lang2 != "": m.lang_iso_639_3_2 = Lang(m.lang2).pt3 def get_coqui_models() -> List[TtsModel]: # English (coqui-ai/TTS) models = [ TtsModel(model_dir="vits-coqui-en-ljspeech"), TtsModel(model_dir="vits-coqui-en-ljspeech-neon"), TtsModel(model_dir="vits-coqui-en-vctk"), # TtsModel(model_dir="vits-coqui-en-jenny"), ] for m in models: m.data_dir = m.model_dir + "/" + "espeak-ng-data" m.model_name = "model.onnx" m.lang = "en" character_models = [ TtsModel(model_dir="vits-coqui-bg-cv", lang="bg"), TtsModel(model_dir="vits-coqui-bn-custom_female", lang="bn"), TtsModel(model_dir="vits-coqui-cs-cv", lang="cs"), TtsModel(model_dir="vits-coqui-da-cv", lang="da"), TtsModel(model_dir="vits-coqui-de-css10", lang="de"), TtsModel(model_dir="vits-coqui-es-css10", lang="es"), TtsModel(model_dir="vits-coqui-et-cv", lang="et"), TtsModel(model_dir="vits-coqui-fi-css10", lang="fi"), TtsModel(model_dir="vits-coqui-fr-css10", lang="fr"), TtsModel(model_dir="vits-coqui-ga-cv", lang="ga"), TtsModel(model_dir="vits-coqui-hr-cv", lang="hr"), TtsModel(model_dir="vits-coqui-lt-cv", lang="lt"), TtsModel(model_dir="vits-coqui-lv-cv", lang="lv"), TtsModel(model_dir="vits-coqui-mt-cv", lang="mt"), TtsModel(model_dir="vits-coqui-nl-css10", lang="nl"), TtsModel(model_dir="vits-coqui-pl-mai_female", lang="pl"), TtsModel(model_dir="vits-coqui-pt-cv", lang="pt"), TtsModel(model_dir="vits-coqui-ro-cv", lang="ro"), TtsModel(model_dir="vits-coqui-sk-cv", lang="sk"), TtsModel(model_dir="vits-coqui-sl-cv", lang="sl"), TtsModel(model_dir="vits-coqui-sv-cv", lang="sv"), TtsModel(model_dir="vits-coqui-uk-mai", lang="uk"), ] for m in character_models: m.is_char = True m.model_name = "model.onnx" return models + character_models def get_piper_models() -> List[TtsModel]: models = [ # TtsModel(model_dir="vits-piper-es_ES-mls_10246-low"), # TtsModel(model_dir="vits-piper-es_ES-mls_9972-low"), # TtsModel(model_dir="vits-piper-pl_PL-mls_6892-low"), TtsModel(model_dir="vits-piper-ar_JO-kareem-low"), TtsModel(model_dir="vits-piper-ar_JO-kareem-medium"), TtsModel(model_dir="vits-piper-ca_ES-upc_ona-medium"), TtsModel(model_dir="vits-piper-ca_ES-upc_ona-x_low"), TtsModel(model_dir="vits-piper-ca_ES-upc_pau-x_low"), TtsModel(model_dir="vits-piper-cs_CZ-jirka-low"), TtsModel(model_dir="vits-piper-cs_CZ-jirka-medium"), TtsModel(model_dir="vits-piper-cy_GB-bu_tts-medium"), TtsModel(model_dir="vits-piper-cy_GB-gwryw_gogleddol-medium"), TtsModel(model_dir="vits-piper-da_DK-talesyntese-medium"), TtsModel(model_dir="vits-piper-de_DE-eva_k-x_low"), TtsModel(model_dir="vits-piper-de_DE-karlsson-low"), TtsModel(model_dir="vits-piper-de_DE-kerstin-low"), # TtsModel(model_dir="vits-piper-de_DE-mls-medium"), TtsModel(model_dir="vits-piper-de_DE-pavoque-low"), TtsModel(model_dir="vits-piper-de_DE-ramona-low"), TtsModel(model_dir="vits-piper-de_DE-thorsten-high"), TtsModel(model_dir="vits-piper-de_DE-thorsten-low"), TtsModel(model_dir="vits-piper-de_DE-thorsten-medium"), TtsModel(model_dir="vits-piper-de_DE-thorsten_emotional-medium"), TtsModel(model_dir="vits-piper-de_DE-glados-high"), TtsModel(model_dir="vits-piper-de_DE-glados-low"), TtsModel(model_dir="vits-piper-de_DE-glados-medium"), TtsModel(model_dir="vits-piper-de_DE-glados_turret-high"), TtsModel(model_dir="vits-piper-de_DE-glados_turret-low"), TtsModel(model_dir="vits-piper-de_DE-glados_turret-medium"), TtsModel(model_dir="vits-piper-el_GR-rapunzelina-low"), TtsModel(model_dir="vits-piper-en_GB-alan-low"), TtsModel(model_dir="vits-piper-en_GB-alan-medium"), TtsModel(model_dir="vits-piper-en_GB-alba-medium"), TtsModel(model_dir="vits-piper-en_GB-aru-medium"), TtsModel(model_dir="vits-piper-en_GB-cori-high"), TtsModel(model_dir="vits-piper-en_GB-cori-medium"), TtsModel(model_dir="vits-piper-en_GB-jenny_dioco-medium"), TtsModel(model_dir="vits-piper-en_GB-northern_english_male-medium"), TtsModel(model_dir="vits-piper-en_GB-semaine-medium"), TtsModel(model_dir="vits-piper-en_GB-southern_english_female-low"), TtsModel(model_dir="vits-piper-en_GB-southern_english_female-medium"), TtsModel(model_dir="vits-piper-en_GB-southern_english_male-medium"), TtsModel(model_dir="vits-piper-en_GB-sweetbbak-amy"), TtsModel(model_dir="vits-piper-en_GB-vctk-medium"), TtsModel(model_dir="vits-piper-en_US-amy-low"), TtsModel(model_dir="vits-piper-en_US-amy-medium"), TtsModel(model_dir="vits-piper-en_US-arctic-medium"), TtsModel(model_dir="vits-piper-en_US-bryce-medium"), TtsModel(model_dir="vits-piper-en_US-danny-low"), TtsModel(model_dir="vits-piper-en_US-glados"), TtsModel(model_dir="vits-piper-en_US-glados-high"), TtsModel(model_dir="vits-piper-en_US-hfc_female-medium"), TtsModel(model_dir="vits-piper-en_US-hfc_male-medium"), TtsModel(model_dir="vits-piper-en_US-joe-medium"), TtsModel(model_dir="vits-piper-en_US-john-medium"), TtsModel(model_dir="vits-piper-en_US-kathleen-low"), TtsModel(model_dir="vits-piper-en_US-kristin-medium"), TtsModel(model_dir="vits-piper-en_US-kusal-medium"), TtsModel(model_dir="vits-piper-en_US-l2arctic-medium"), TtsModel(model_dir="vits-piper-en_US-lessac-high"), TtsModel(model_dir="vits-piper-en_US-lessac-low"), TtsModel(model_dir="vits-piper-en_US-lessac-medium"), TtsModel(model_dir="vits-piper-en_US-libritts-high"), TtsModel(model_dir="vits-piper-en_US-libritts_r-medium"), TtsModel(model_dir="vits-piper-en_US-ljspeech-high"), TtsModel(model_dir="vits-piper-en_US-ljspeech-medium"), TtsModel(model_dir="vits-piper-en_US-norman-medium"), TtsModel(model_dir="vits-piper-en_US-ryan-high"), TtsModel(model_dir="vits-piper-en_US-ryan-low"), TtsModel(model_dir="vits-piper-en_US-ryan-medium"), TtsModel(model_dir="vits-piper-es_ES-carlfm-x_low"), TtsModel(model_dir="vits-piper-es_ES-davefx-medium"), TtsModel(model_dir="vits-piper-es_ES-glados-medium"), TtsModel(model_dir="vits-piper-es_ES-sharvard-medium"), TtsModel(model_dir="vits-piper-es_MX-ald-medium"), TtsModel(model_dir="vits-piper-es_MX-claude-high"), TtsModel(model_dir="vits-piper-fa_IR-amir-medium"), TtsModel(model_dir="vits-piper-fa_IR-ganji-medium"), TtsModel(model_dir="vits-piper-fa_IR-ganji_adabi-medium"), TtsModel(model_dir="vits-piper-fa_IR-gyro-medium"), TtsModel(model_dir="vits-piper-fa_IR-reza_ibrahim-medium"), TtsModel(model_dir="vits-piper-fa_en-rezahedayatfar-ibrahimwalk-medium"), TtsModel(model_dir="vits-piper-fi_FI-harri-low"), TtsModel(model_dir="vits-piper-fi_FI-harri-medium"), # TtsModel(model_dir="vits-piper-fr_FR-mls-medium"), TtsModel(model_dir="vits-piper-fr_FR-gilles-low"), TtsModel(model_dir="vits-piper-fr_FR-siwis-low"), TtsModel(model_dir="vits-piper-fr_FR-siwis-medium"), TtsModel(model_dir="vits-piper-fr_FR-tom-medium"), TtsModel(model_dir="vits-piper-fr_FR-upmc-medium"), TtsModel(model_dir="vits-piper-hu_HU-anna-medium"), TtsModel(model_dir="vits-piper-hu_HU-berta-medium"), TtsModel(model_dir="vits-piper-hu_HU-imre-medium"), TtsModel(model_dir="vits-piper-is_IS-bui-medium"), TtsModel(model_dir="vits-piper-is_IS-salka-medium"), TtsModel(model_dir="vits-piper-is_IS-steinn-medium"), TtsModel(model_dir="vits-piper-is_IS-ugla-medium"), TtsModel(model_dir="vits-piper-it_IT-paola-medium"), TtsModel(model_dir="vits-piper-it_IT-riccardo-x_low"), TtsModel(model_dir="vits-piper-ka_GE-natia-medium"), TtsModel(model_dir="vits-piper-kk_KZ-iseke-x_low"), TtsModel(model_dir="vits-piper-kk_KZ-issai-high"), TtsModel(model_dir="vits-piper-kk_KZ-raya-x_low"), TtsModel(model_dir="vits-piper-lv_LV-aivars-medium"), TtsModel(model_dir="vits-piper-lb_LU-marylux-medium"), TtsModel(model_dir="vits-piper-ne_NP-chitwan-medium"), TtsModel(model_dir="vits-piper-ne_NP-google-medium"), TtsModel(model_dir="vits-piper-ne_NP-google-x_low"), TtsModel(model_dir="vits-piper-nl_BE-nathalie-medium"), TtsModel(model_dir="vits-piper-nl_BE-nathalie-x_low"), TtsModel(model_dir="vits-piper-nl_BE-rdh-medium"), TtsModel(model_dir="vits-piper-nl_BE-rdh-x_low"), # TtsModel(model_dir="vits-piper-nl_NL-mls-medium"), # TtsModel(model_dir="vits-piper-nl_NL-mls_5809-low"), # TtsModel(model_dir="vits-piper-nl_NL-mls_7432-low"), TtsModel(model_dir="vits-piper-no_NO-talesyntese-medium"), TtsModel(model_dir="vits-piper-pl_PL-darkman-medium"), TtsModel(model_dir="vits-piper-pl_PL-gosia-medium"), TtsModel(model_dir="vits-piper-pl_PL-mc_speech-medium"), TtsModel(model_dir="vits-piper-pt_BR-cadu-medium"), TtsModel(model_dir="vits-piper-pt_BR-edresson-low"), TtsModel(model_dir="vits-piper-pt_BR-faber-medium"), TtsModel(model_dir="vits-piper-pt_BR-jeff-medium"), TtsModel(model_dir="vits-piper-pt_PT-tugao-medium"), TtsModel(model_dir="vits-piper-ro_RO-mihai-medium"), TtsModel(model_dir="vits-piper-ru_RU-denis-medium"), TtsModel(model_dir="vits-piper-ru_RU-dmitri-medium"), TtsModel(model_dir="vits-piper-ru_RU-irina-medium"), TtsModel(model_dir="vits-piper-ru_RU-ruslan-medium"), TtsModel(model_dir="vits-piper-sk_SK-lili-medium"), TtsModel(model_dir="vits-piper-sl_SI-artur-medium"), TtsModel(model_dir="vits-piper-sr_RS-serbski_institut-medium"), TtsModel(model_dir="vits-piper-sv_SE-lisa-medium"), TtsModel(model_dir="vits-piper-sv_SE-nst-medium"), TtsModel(model_dir="vits-piper-sw_CD-lanfrica-medium"), TtsModel(model_dir="vits-piper-tr_TR-dfki-medium"), TtsModel(model_dir="vits-piper-tr_TR-fahrettin-medium"), TtsModel(model_dir="vits-piper-tr_TR-fettah-medium"), TtsModel(model_dir="vits-piper-uk_UA-lada-x_low"), TtsModel(model_dir="vits-piper-uk_UA-ukrainian_tts-medium"), TtsModel(model_dir="vits-piper-vi_VN-25hours_single-low"), TtsModel(model_dir="vits-piper-vi_VN-vais1000-medium"), TtsModel(model_dir="vits-piper-vi_VN-vivos-x_low"), TtsModel(model_dir="vits-piper-zh_CN-huayan-medium"), ] for m in models: m.data_dir = m.model_dir + "/" + "espeak-ng-data" m.model_name = m.model_dir[len("vits-piper-") :] + ".onnx" m.lang = m.model_dir.split("-")[2][:2] return models def get_mimic3_models() -> List[TtsModel]: models = [ TtsModel(model_dir="vits-mimic3-af_ZA-google-nwu_low"), TtsModel(model_dir="vits-mimic3-bn-multi_low"), TtsModel(model_dir="vits-mimic3-es_ES-m-ailabs_low"), TtsModel(model_dir="vits-mimic3-fa-haaniye_low"), TtsModel(model_dir="vits-mimic3-fi_FI-harri-tapani-ylilammi_low"), TtsModel(model_dir="vits-mimic3-gu_IN-cmu-indic_low"), TtsModel(model_dir="vits-mimic3-hu_HU-diana-majlinger_low"), TtsModel(model_dir="vits-mimic3-ko_KO-kss_low"), TtsModel(model_dir="vits-mimic3-ne_NP-ne-google_low"), TtsModel(model_dir="vits-mimic3-pl_PL-m-ailabs_low"), TtsModel(model_dir="vits-mimic3-tn_ZA-google-nwu_low"), TtsModel(model_dir="vits-mimic3-vi_VN-vais1000_low"), ] for m in models: m.data_dir = m.model_dir + "/" + "espeak-ng-data" m.model_name = m.model_dir[len("vits-mimic3-") :] + ".onnx" m.lang = m.model_dir.split("-")[2][:2] return models def get_vits_models() -> List[TtsModel]: chinese_models = [ # Chinese TtsModel( model_dir="vits-icefall-zh-aishell3", model_name="model.onnx", lang="zh", rule_fsts="vits-icefall-zh-aishell3/phone.fst,vits-icefall-zh-aishell3/date.fst,vits-icefall-zh-aishell3/number.fst,vits-icefall-zh-aishell3/new_heteronym.fst", rule_fars="vits-icefall-zh-aishell3/rule.far", ), TtsModel( model_dir="vits-zh-aishell3", model_name="vits-aishell3.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-doom", model_name="doom.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-echo", model_name="echo.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-zenyatta", model_name="zenyatta.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-abyssinvoker", model_name="abyssinvoker.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-keqing", model_name="keqing.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-eula", model_name="eula.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-bronya", model_name="bronya.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-theresa", model_name="theresa.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-fanchen-wnj", model_name="vits-zh-hf-fanchen-wnj.onnx", lang="zh", ), TtsModel( model_dir="vits-melo-tts-zh_en", model_name="model.onnx", lang="zh", lang2="en", ), TtsModel( model_dir="vits-zh-hf-fanchen-C", model_name="vits-zh-hf-fanchen-C.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-fanchen-ZhiHuiLaoZhe", model_name="vits-zh-hf-fanchen-ZhiHuiLaoZhe.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-fanchen-ZhiHuiLaoZhe_new", model_name="vits-zh-hf-fanchen-ZhiHuiLaoZhe_new.onnx", lang="zh", ), TtsModel( model_dir="vits-zh-hf-fanchen-unity", model_name="vits-zh-hf-fanchen-unity.onnx", lang="zh", ), TtsModel( model_dir="sherpa-onnx-vits-zh-ll", model_name="model.onnx", lang="zh", ), ] rule_fsts = ["phone.fst", "date.fst", "number.fst"] for m in chinese_models: s = [f"{m.model_dir}/{r}" for r in rule_fsts] if ( "vits-zh-hf" in m.model_dir or "sherpa-onnx-vits-zh-ll" == m.model_dir or "melo-tts" in m.model_dir ): s = s[:-1] m.dict_dir = m.model_dir + "/dict" else: m.rule_fars = f"{m.model_dir}/rule.far" m.rule_fsts = ",".join(s) all_models = chinese_models + [ TtsModel( model_dir="vits-cantonese-hf-xiaomaiiwn", model_name="vits-cantonese-hf-xiaomaiiwn.onnx", lang="cantonese", lang_iso_639_3="yue", rule_fsts="vits-cantonese-hf-xiaomaiiwn/rule.fst", ), # English (US) TtsModel(model_dir="vits-vctk", model_name="vits-vctk.onnx", lang="en"), # TtsModel(model_dir="vits-ljs", model_name="vits-ljs.onnx", lang="en"), # fmt: on ] return all_models def get_matcha_models() -> List[TtsModel]: chinese_models = [ TtsModel( model_dir="matcha-icefall-zh-baker", acoustic_model_name="model-steps-3.onnx", lang="zh", ) ] rule_fsts = ["phone.fst", "date.fst", "number.fst"] for m in chinese_models: s = [f"{m.model_dir}/{r}" for r in rule_fsts] m.rule_fsts = ",".join(s) m.dict_dir = m.model_dir + "/dict" m.vocoder = "vocos-22khz-univ.onnx" english_persian_models = [ TtsModel( model_dir="matcha-icefall-en_US-ljspeech", acoustic_model_name="model-steps-3.onnx", lang="en", ), TtsModel( model_dir="matcha-tts-fa_en-musa", acoustic_model_name="model.onnx", lang="fa", ), TtsModel( model_dir="matcha-tts-fa_en-khadijah", acoustic_model_name="model.onnx", lang="fa", ), ] for m in english_persian_models: m.data_dir = f"{m.model_dir}/espeak-ng-data" m.vocoder = "vocos-22khz-univ.onnx" return chinese_models + english_persian_models def get_kokoro_models() -> List[TtsModel]: english_models = [ TtsModel( model_dir="kokoro-en-v0_19", model_name="model.onnx", lang="en", ) ] for m in english_models: m.data_dir = f"{m.model_dir}/espeak-ng-data" m.voices = "voices.bin" multi_lingual_models = [ TtsModel( model_dir="kokoro-multi-lang-v1_0", model_name="model.onnx", lang="en", lang2="zh", ), TtsModel( model_dir="kokoro-multi-lang-v1_1", model_name="model.onnx", lang="en", lang2="zh", ), TtsModel( model_dir="kokoro-int8-multi-lang-v1_1", model_name="model.int8.onnx", lang="en", lang2="zh", ), ] for m in multi_lingual_models: m.data_dir = f"{m.model_dir}/espeak-ng-data" m.dict_dir = f"{m.model_dir}/dict" m.voices = "voices.bin" m.lexicon = f"{m.model_dir}/lexicon-us-en.txt,{m.model_dir}/lexicon-zh.txt" m.rule_fsts = f"{m.model_dir}/phone-zh.fst,{m.model_dir}/date-zh.fst,{m.model_dir}/number-zh.fst" return english_models + multi_lingual_models def main(): args = get_args() index = args.index total = args.total assert 0 <= index < total, (index, total) d = dict() all_model_list = get_vits_models() all_model_list += get_piper_models() all_model_list += get_mimic3_models() all_model_list += get_coqui_models() all_model_list += get_matcha_models() all_model_list += get_kokoro_models() convert_lang_to_iso_639_3(all_model_list) print(all_model_list) num_models = len(all_model_list) num_per_runner = num_models // total if num_per_runner <= 0: raise ValueError(f"num_models: {num_models}, num_runners: {total}") start = index * num_per_runner end = start + num_per_runner remaining = num_models - args.total * num_per_runner print(f"{index}/{total}: {start}-{end}/{num_models}") d["tts_model_list"] = all_model_list[start:end] if index < remaining: s = args.total * num_per_runner + index d["tts_model_list"].append(all_model_list[s]) print(f"{s}/{num_models}") filename_list = ["./build-apk-tts.sh", "./build-apk-tts-engine.sh"] for filename in filename_list: environment = jinja2.Environment() with open(f"{filename}.in") as f: s = f.read() template = environment.from_string(s) s = template.render(**d) with open(filename, "w") as f: print(s, file=f) if __name__ == "__main__": main()