On-device AI Models to Convert Voice to Text in French

TLDR: Transformez des paroles en texte grâce à l'IA de Picovoice

Picovoice offre deux modèles Speech-to-Text sur l'appareil : asynchrone et en temps réel. Selon le besoin de transcription -en post-traitement ou en temps réel- vous soumettez des données audio et recevez les résultats sous forme de texte, sans latence réseau ni compromettre la confidentialité des utilisateurs.

Picovoice’s on-device speech-to-text models, Leopard and Cheetah, now support French. Speech-to-text, also known as automatic speech recognition (ASR), makes it easy to add audio and video transcription to applications. Enterprises can now create text transcripts of audio and video input quickly without jeopardizing user privacy or worrying about user experience.

Zero-latency, real-time transcription in French

Similar to cloud real-time transcription APIs, Cheetah Streaming Speech-to-Text empowers enterprises to increase the accessibility and discoverability of their audio and video content - whether it’s a live event, online meeting, or medical dictation.

With its unique on-device and streaming voice data processing capability, Cheetah Streaming Speech-to-Text elevates the user experience and enables new use cases that hadn’t been possible before. Contact centers can automate certain inquiries and provide agents with real-time coaching. Online meeting providers can add real-time speech-to-speech translation along with real-time transcription.

What makes French Cheetah Streaming Speech-to-Text unique?

Cheetah Streaming Speech-to-Text processes voice data locally and in real time, enabling “real” real-time applications.

1. Zero network latency: Unlike cloud transcription APIs, such as AWS Transcribe and Google Speech-to-Text, it does not send voice data to remote servers to get it transcribed, eliminating the latency in voice AI applications.
2. Streaming data processing: Unlike state-of-the-art on-device transcription engines, such as Whisper, Cheetah is designed to handle streaming voice input, eliminating the limitations for real-time applications.

To learn more, visit Cheetah Streaming Speech-to-Text platform page or start building with your favorite SDK!

o = pvcheetah.create(access_key)

partial_transcript, is_endpoint =
  o.process(get_next_audio_frame())
Build with Python

Choosing the best French Speech-to-Text

Evaluate Cheetah Streaming Speech-to-Text accuracy by comparing it against popular asynchronous French speech-to-text models using our open-source French speech-to-text benchmark.

Comparez les modèles Picovoice Cheetah, Whisper, Amazon Transcribe et Google Speech-to-text en français. Choisissez celui qui convient le mieux à votre candidature!

Custom French Speech-to-Text Models

Legal terminology is different from healthcare. Customize the default French model for your domain and application. Improving Cheetah Streaming Speech-to-Text accuracy by using Picovoice Console’s type-and-train interface does not require knowledge of Machine Learning.

Visit Leopard Speech-to-Text platform page if you’re interested in converting French audio and video files to text using asynchronous speech-to-text that achieves cloud-level accuracy without jeopardizing user privacy!