Article 641B0 OpenAI Open-Sources Whisper, a Multilingual Speech Recognition System

OpenAI Open-Sources Whisper, a Multilingual Speech Recognition System

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BeauHD
from Slashdot on (#641B0)
Speech recognition remains a challenging problem in AI and machine learning. In a step toward solving it, OpenAI today open-sourced Whisper, an automatic speech recognition system that the company claims enables "robust" transcription in multiple languages as well as translation from those languages into English. TechCrunch reports: Countless organizations have developed highly capable speech recognition systems, which sit at the core of software and services from tech giants like Google, Amazon and Meta. But what makes Whisper different, according to OpenAI, is that it was trained on 680,000 hours of multilingual and "multitask" data collected from the web, which lead to improved recognition of unique accents, background noise and technical jargon. "The primary intended users of [the Whisper] models are AI researchers studying robustness, generalization, capabilities, biases and constraints of the current model. However, Whisper is also potentially quite useful as an automatic speech recognition solution for developers, especially for English speech recognition," OpenAI wrote in the GitHub repo for Whisper, from where several versions of the system can be downloaded. "[The models] show strong ASR results in ~10 languages. They may exhibit additional capabilities ... if fine-tuned on certain tasks like voice activity detection, speaker classification or speaker diarization but have not been robustly evaluated in these area." Whisper has its limitations, particularly in the area of text prediction. Because the system was trained on a large amount of "noisy" data, OpenAI cautions Whisper might include words in its transcriptions that weren't actually spoken -- possibly because it's both trying to predict the next word in audio and trying to transcribe the audio itself. Moreover, Whisper doesn't perform equally well across languages, suffering from a higher error rate when it comes to speakers of languages that aren't well-represented in the training data. Despite this, OpenAI sees Whisper's transcription capabilities being used to improve existing accessibility tools.

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