Speech-to-Text

Overview

Speech-to-text models convert spoken language into written text, enabling voice-based interactions across various applications. These models leverage deep learning techniques, such as recurrent neural networks (RNNs) and transformers, to process audio signals and transcribe them with high accuracy. They are commonly used in voice assistants, transcription services, and accessibility tools, supporting multiple languages and adapting to different accents and speech patterns.

Quick Code Examples

Let's use the #g1_whisper-large model to transcribe the following audio fragment:

Example #1: Processing a Speech Audio File via URL

Response

Example #2: Processing a Speech Audio File via File Path

Response

All Available Speech-to-Text Models

Last updated

Was this helpful?