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Whistle: Speech to Text in 16.9 MB (cactuscompute.com)

946 points by gmays · 2 days ago · 181 comments on HN

Article summary

Whistle is a new open speech recognition model that can run on devices with limited resources, such as mobiles and microcontrollers. It can transcribe speech in seven languages and has a small binary size of 16.9 MB. The model is designed to work with the Needle engine and can be used for various applications, including speech-to-text and voice control. Whistle's performance is comparable to other models, but its small size and low latency make it suitable for real-time applications.

Main themes

  • Speech Recognition
  • Model Size
  • On-Device Processing
  • Language Support
  • Accent and Dialect
  • Dictation Models
  • Audio Quality
  • Latency and Privacy

What commenters say

  • Some users find Whistle to be highly accurate, especially for English speech, while others experience difficulties with non-English languages or accents.
  • The challenge of speech-to-text lies not only in model size, but also in data scarcity, irregular speech patterns, and individual differences.
  • Small models like Whistle can enable on-device speech recognition, which is important for privacy and latency-sensitive applications, but may compromise on quality.
  • The use of speech-to-text models can be improved by combining them with other technologies, such as language models, to clean up transcripts and improve accuracy.
  • Some users prefer to use dictation models specifically designed for writing and editing, rather than general-purpose speech-to-text models.
  • The quality of speech recognition can be affected by various factors, including audio quality, vocabulary, and context.
  • There are differing opinions on the importance of model size, with some arguing that it is a key factor in enabling on-device processing, while others see it as just one aspect of the overall challenge.
  • The development of speech-to-text models can have a significant impact on individuals with speech disorders or disabilities, and more research is needed to address the specific challenges they face.