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Talk · Optical Fibers and Their Applications · December 20, 2023

Neurorecognition visualization in multitask end-to-end speech

Orken J. Mamyrbayev, Sergii V. Pavlov, Akbayan Bekarystankyzy, Дина Оралбекова, Багашар Жумажанов, Larysa Аzarova

Orken Mamyrbayev
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Abstract

Nowadays, speech-processing technologies with different language systems are successfully used in mobile and stationary devices. Kazakh is considered a low-resource language, which poses various challenges for conventional speech recognition methods. This paper presents a proposed model capable of multitasking and handling concurrent speech recognition, dialect identification, and speaker identification, all in an end-to-end framework. The developed multitask model enables training three different tasks within a single model. A multitask recognition system is created based on the WaveNet-CTC model. Experiments show that for the concrete task end-to-end multitask model has better performance than other models.

Speech Recognition and SynthesisSpeech and Audio ProcessingSpeech and dialogue systemsend-to-end speech recognitionmulti-task learningKazakh language

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