The development of acoustic models for command and control arabic speech recognition system

2005 ◽  
Author(s):  
M. Nofal ◽  
E. Abdel Reheem ◽  
H. El Henawy ◽  
N. Abdel Kader
Keyword(s):  
Speech Recognition ◽  
Command And Control ◽  
Recognition System ◽  
Speech Recognition System ◽  
Acoustic Models ◽  
And Control ◽  
Arabic Speech Recognition

scholarly journals The Challenges of Developing a Living Arabic Phonetic Dictionary for Speech Recognition System: A Literature Review

2021 ◽  
Vol 8 (1) ◽  
pp. 164-170
Author(s):  
Mohammad Husam Alhumsi ◽  
Saleh Belhassen
Keyword(s):  
Speech Recognition ◽  
Literature Review ◽  
Recognition System ◽  
Speech Recognition System ◽  
System A ◽  
Normal Human ◽  
Recognition Systems ◽  
Translation Systems ◽  
Arabic Speech Recognition

Phonetic dictionaries are regarded as pivotal components of speech recognition systems. The function of speech recognition research is to generate a machine which will accurately identify and distinguish the normal human speech from any other speaker. Literature affirmed that Arabic phonetics is one of the major problems in Arabic speech recognition. Therefore, this paper reviews previous studies tackling the challenges faced by initiating an Arabic phonetic dictionary with respect to Arabic speech recognition. It has been found that the system of speech recognition investigated areas of differences concerning Arabic phonetics. In addition, an Arabic phonetic dictionary should be initiated where the Arabic vowels’ phonemes should be considered as a component of the consonants’ phonemes. Thus, the incorporation of developed machine translation systems may enhance the quality of the system. The current paper concludes with the existing challenges faced by Arabic phonetic dictionary.

scholarly journals Triphone Model Based Novel Kannada Continuous Speech Recognition System using Kaldi Tool

2020 ◽  
Vol 9 (9) ◽  
pp. 452-458
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Recognition System ◽  
Speech Recognition System ◽  
Acoustic Model ◽  
Mel Frequency Cepstral Coefficients ◽  
Automatic Speech Recognition System ◽  
Data Set ◽  
Acoustic Models ◽  
Recognition Systems

Accent is one of the issue for speech recognition systems. Automatic Speech Recognition systems must yield high performance for different dialects. In this work, Neutral Kannada Automatic Speech Recognition is implemented using Kaldi software for monophone modelling and triphone modeling. The acoustic models are constructed using the techniques such as monophone, triphone1, triphone2, triphone3. In triphone modeling, grouping of interphones is performed. Feature extraction is performed by Mel Frequency Cepstral Coefficients. The system performance is analysed by measuring Word Error Rate using different acoustic models. To know the robustness and performance of the Neutral Kannada Automatic Speech Recognition system for different dialects in Kannada, the system is tested for North Kannada accent. Better sentence accuracy is obtained for Neutral Kannada Automatic Speech Recognition system and is about 90%. The performance is degraded, when tested for North Kannada accent and the accuracy obtained is around 77%. The performance is degraded due to the increasing mismatch between the training and testing data set, as the Neutral Kannada Automatic Speech Recognition system is trained only for neutral Kannada acoustic model and doesn't include north Kannada acoustic model. Interactive Kannada voice response system is implemented to identify continuous Kannada speech sentences.

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