Target-Directed Mixture Dynamic Models for Spontaneous Speech Recognition

2004 ◽  
Vol 12 (1) ◽  
pp. 47-58 ◽  
Author(s):  
J.Z. Ma ◽  
L. Deng
Keyword(s):  
Speech Recognition ◽  
Dynamic Models ◽  
Spontaneous Speech

Combinations of various language model technologies including data expansion and adaptation in spontaneous speech recognition

2015 ◽  
Author(s):  
Ryo Masumura ◽  
Taichi Asami ◽  
Takanobu Oba ◽  
Hirokazu Masataki ◽  
Sumitaka Sakauchi ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Language Model ◽  
Spontaneous Speech ◽  
Data Expansion

scholarly journals Vocabulary Size Influences Spontaneous Speech in Native Language Users: Validating the Use of Automatic Speech Recognition in Individual Differences Research

2020 ◽  
pp. 002383092091107 ◽  
Author(s):  
Suzanne R. Jongman ◽  
Yung Han Khoe ◽  
Florian Hintz
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Language Production ◽  
Spontaneous Speech ◽  
Receptive Vocabulary ◽  
Sentence Production ◽  
Production Data ◽  
Vocabulary Size ◽  
Speech Transcription ◽  
The Relationship

Previous research has shown that vocabulary size affects performance on laboratory word production tasks. Individuals who know many words show faster lexical access and retrieve more words belonging to pre-specified categories than individuals who know fewer words. The present study examined the relationship between receptive vocabulary size and speaking skills as assessed in a natural sentence production task. We asked whether measures derived from spontaneous responses to everyday questions correlate with the size of participants’ vocabulary. Moreover, we assessed the suitability of automatic speech recognition (ASR) for the analysis of participants’ responses in complex language production data. We found that vocabulary size predicted indices of spontaneous speech: individuals with a larger vocabulary produced more words and had a higher speech-silence ratio compared to individuals with a smaller vocabulary. Importantly, these relationships were reliably identified using manual and automated transcription methods. Taken together, our results suggest that spontaneous speech elicitation is a useful method to investigate natural language production and that automatic speech recognition can alleviate the burden of labor-intensive speech transcription.

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