Acoustic Word Embeddings for Low Resource Speech Processing with Herman Kamper – TWiML Talk #191
In this episode of our Deep Learning Indaba Series, we’re joined by Herman Kamper, Lecturer in the electrical and electronics engineering department at Stellenbosch University in SA and a co-organizer of the Indaba.
Herman and I discuss his work on limited- and zero-resource speech recognition, how those differ from regular speech recognition, and the tension between linguistic and statistical methods in this space. We dive into the specifics of the methods being used and developed in Herman’s lab as well, including how phoneme data is used for segmenting and processing speech data.
The full show notes for this episode can be found at https://twimlai.com/talk/191.
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