Author's): Gowtham Boyina
Originally published in Towards Artificial Intelligence.
The forced alignment model is the interesting part
Over time, I have tested dozens of speech recognition models. Most claim to support multilingualism, but it quietly falls apart when you feed them actual Chinese dialects, accented English, or anything other than the standard broadcast audio. The ones that work well are usually proprietary APIs that scale uncomfortably.
Alibaba's Qwen team introduced Qwen3-ASR, an open-source speech recognition system that supports 52 languages and dialects. Key models include Qwen3-ASR-1.7B, which boasts state-of-the-art performance for multilingual tasks, and Qwen3-ForcedAligner-0.6B, a non-autoregressive model for accurate speech and text alignment. These improvements enable better support for Chinese dialects, user-generated content in multiple languages, and improved timestamp accuracy for applications requiring precise audio-text synchronization.
Read the entire blog for free on Medium.
Published via Towards AI
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