Multilingual Speech Processing

By G. B. Varile. 2005

Subfields: Computational Linguistics & Semantics, Speech & Audio

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Citations in the corpus

Robust Speech Recognition via Large-Scale Weak Supervision (2022, methodology): “In speech recognition, multi-lingual models have been explored for well over a decade (Schultz & Kirchhoff, 2006).”
Bytes Are All You Need: End-to-end Multilingual Speech Recognition and Synthesis with Bytes (2018, background): “Expanding the coverage of the world’s languages in Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems have been attracting much interest in both academia and industry [1, 2].”
Multilingual representations for low resource speech recognition and keyword search (2015, unknown): “In deriving multilingual representations, there have been studies focussed on carefully identifying a subset of language(s) closest to the target language [26, 27], with subsequent use of data from this subset only for training the network.”
Brain-to-text: decoding spoken phrases from phone representations in the brain (2015, methodology): “Following a common idea of modern speech recognition technology (Rabiner, 1989; Schultz and Kirchhoﬀ, 2006), we combined the information about the observed neural activity with statistical language information during the decoding process by Bayesian updating (Rabiner, 1989).”
Textless Direct Speech-to-Speech Translation with Discrete Speech Representation (2022, background): “However, the vast majority of the approximately 7,000 languages in the world do not have speech recognition systems or even acknowledged written forms [5–7].”