Blog(7)
Automatic Speech Recognition (ASR) system is a critical element in many applications, including voice assistants, transcription services, and speech-to-text technology.
Nowadays, voice assistants have been widely used by users to control smart phones. An automatic speech recognition (ASR) model plays a crucial role in the voice assistant system to recognise the user voice command, which is subsequently used for downstream tasks such as spoken language understanding and speech translation.
The clashing of pans and pots as you cook and ask your voice assistant what you can use to replace eggs in the recipe. The excited, overlapping conversations as you ask which of Henry the VIIIs wives survived, trying to settle a bet.
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Publications(34)
Benchmarking Rotary Position Embeddings for Automatic Speech Recognition
AuthorShucong Zhang, Titouan Parcollet, Rogier van Dalen,
PublishedIEEE Workshop on Automatic Speech Recognition & Understanding (ASRU)
Date2025-12-06
Evaluation of LLMs in Speech is Often Flawed: Test Set Contamination in Large Language Models for Speech Recognition
AuthorTitouan Parcollet, Rogier van Dalen, Shucong Zhang
Loquacious Set: 25,000 Hours of Transcribed and Diverse English Speech Recognition Data for Research and Commercial Use
AuthorTitouan Parcollet, Shucong Zhang, Rogier van Dalen
PublishedAnnual Conference of the International Speech Communication Association (INTERSPEECH)
Date2025-08-18
News(12)
Multilingual Automatic Speech Recognition (ASR) presents several challenges, especially when multiple languages are being spoken in the same audio.
Personalizing automated speech recognition (ASR) for voice assistant systems is often considered the holy grail, requiring meticulous attention to detail in model optimization.
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