微软 MAI-Transcribe-1.5 发布：支持关键词偏置，FLEURS 上 WER 降低 30%
Introducing MAI-Transcribe-1.5
微软推出转录模型 MAI-Transcribe-1.5，新增关键词偏置功能，可让用户提供人名、产品名、医学术语等特定领域词汇列表来引导预测，模型会结合上下文判断是否应用偏置而非强行匹配。在 FLEURS 多语言基准上，启用关键词偏置后词错误率（WER）降低 30%，同时保持通用语音的识别准确率。
Keyword biasing
A major challenge for many transcription models is when they fail on domain specific words, which often matter the most to users. These often include people and product names, medical terms, internal acronyms, and customer-specific vocabulary which are critical for enterprises.
MAI-Transcribe-1.5 can now bias its predictions toward a list of domain specific keywords provided by the user. The model does not blindly force matches, it uses the shared context to decide when keyword biasing should apply. This dramatically improves recognition of specialized vocabulary while maintaining accuracy on general speech.
When using the keyword biasing, we observe a 30% reduction in Word-Error-Rate (WER) on the FLEURS multilingual benchmark.
English
Without keyword biasing
So, um, for the next phase, Sean will, uh, take care of the documentation. Oif, right, uh, she’ll handle the user testing sessions. Societal is, um, leading the workflow design. Soren will, uh, set up the analytics, and Niamh is going to coordinate the deployment timeline.
With keyword biasing
List of keywords: “Aisling, Shaun, Xochitl, Ljubiša, Søren, Siobhán, Jorge, Nguyễn Phúc, Aoife, Tadhg, Ghislaine, Niamh, Szczepan, Eoin, Kseniya, Wojciech, Xavier, Maoz”
So, um, for the next phase, Shaun will, uh, take care of the documentation. Aoife, right, uh, she’ll handle the user testing sessions. Xochitl is, um, leading the workflow design. Søren will, uh, set up the analytics, and Niamh is going to coordinate the deployment timeline.
来源：Microsoft AI：官方博客 · microsoft.ai