Ant Group’s Bailing has open-sourced 5 voice models: Its 500-million-parameter TTS model ranked first among open-source equivalents in same-tone blind listening tests.
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Beating AI News: Ant Group has open-sourced its Ming-3.0 voice model series, spanning three core domains—speech synthesis, audio understanding, and speech recognition—with a total of five models: 2 TTS, 2 Audio, and 1 ASR, all released under the MIT license. Developers can combine these models to build functions like voice input, content analysis, and voice responses. The standout is the 500-million-parameter Ming-3.0-tts-0.5B. Users can use natural language to command the AI to adjust tone (e.g., sounding angry), emphasize specific words, or modify speech rhythm. It also supports voice cloning, custom tone design, and inserting 14 sound tags (such as soft laughs and sighs) at designated positions. In Artificial Analysis’ same-voice blind listening test, the model ranks first among open-source models with an Elo score of 1069. The audio understanding model, Ming-3.0-audio-flash, is far larger, with 126 billion total parameters and ~6.5 billion active parameters per activation. It can directly process meeting recordings to answer questions, summarize consensus, disagreements, and action items without generating a separate transcript first. Another model, Ming-3.0-asr-tiny, specializes in speech recognition, supporting input of names, place names, industry terms, and conversation context to aid dialect and rare word recognition. Across four speech recognition tests conducted by Ant Group, its average error rate is 4.41%.
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