Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition
In building speech recognition based applications, robustness to different noisy background condition is an important challenge. In this paper bimodal approach is proposed to improve the robustness of Hindi speech recognition system. Also an importance of different types of visual features is studie...
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| Format: | Article |
| Language: | English |
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Institute of Fundamental Technological Research Polish Academy of Sciences
2015-09-01
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| Series: | Archives of Acoustics |
| Subjects: | |
| Online Access: | https://acoustics.ippt.pan.pl/index.php/aa/article/view/1607 |
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| author | Prashant UPADHYAYA Omar FAROOQ Musiur Raza ABIDI Priyanka VARSHNEY |
| author_facet | Prashant UPADHYAYA Omar FAROOQ Musiur Raza ABIDI Priyanka VARSHNEY |
| author_sort | Prashant UPADHYAYA |
| collection | DOAJ |
| description | In building speech recognition based applications, robustness to different noisy background condition is an important challenge. In this paper bimodal approach is proposed to improve the robustness of Hindi speech recognition system. Also an importance of different types of visual features is studied for audio visual automatic speech recognition (AVASR) system under diverse noisy audio conditions. Four sets of visual feature based on Two-Dimensional Discrete Cosine Transform feature (2D-DCT), Principal Component Analysis (PCA), Two-Dimensional Discrete Wavelet Transform followed by DCT (2D-DWT-DCT) and Two-Dimensional Discrete Wavelet Transform followed by PCA (2D-DWT-PCA) are reported. The audio features are extracted using Mel Frequency Cepstral coefficients (MFCC) followed by static and dynamic feature. Overall, 48 features, i.e. 39 audio features and 9 visual features are used for measuring the performance of the AVASR system. Also, the performance of the AVASR using noisy speech signal generated by using NOISEX database is evaluated for different Signal to Noise ratio (SNR: 30 dB to -10 dB) using Aligarh Muslim University Audio Visual (AMUAV) Hindi corpus. AMUAV corpus is Hindi continuous speech high quality audio visual databases of Hindi sentences spoken by different subjects. |
| format | Article |
| id | doaj-art-c23b904789564468b78fc74b1fe27e7f |
| institution | DOAJ |
| issn | 0137-5075 2300-262X |
| language | English |
| publishDate | 2015-09-01 |
| publisher | Institute of Fundamental Technological Research Polish Academy of Sciences |
| record_format | Article |
| series | Archives of Acoustics |
| spelling | doaj-art-c23b904789564468b78fc74b1fe27e7f2025-08-20T03:13:08ZengInstitute of Fundamental Technological Research Polish Academy of SciencesArchives of Acoustics0137-50752300-262X2015-09-0140410.1515/aoa-2015-0061Comparative Study of Visual Feature for Bimodal Hindi Speech RecognitionPrashant UPADHYAYA0Omar FAROOQ1Musiur Raza ABIDI2Priyanka VARSHNEY3Aligarh Muslim UniversityAligarh Muslim UniversityAligarh Muslim UniversityMindz TechnologyIn building speech recognition based applications, robustness to different noisy background condition is an important challenge. In this paper bimodal approach is proposed to improve the robustness of Hindi speech recognition system. Also an importance of different types of visual features is studied for audio visual automatic speech recognition (AVASR) system under diverse noisy audio conditions. Four sets of visual feature based on Two-Dimensional Discrete Cosine Transform feature (2D-DCT), Principal Component Analysis (PCA), Two-Dimensional Discrete Wavelet Transform followed by DCT (2D-DWT-DCT) and Two-Dimensional Discrete Wavelet Transform followed by PCA (2D-DWT-PCA) are reported. The audio features are extracted using Mel Frequency Cepstral coefficients (MFCC) followed by static and dynamic feature. Overall, 48 features, i.e. 39 audio features and 9 visual features are used for measuring the performance of the AVASR system. Also, the performance of the AVASR using noisy speech signal generated by using NOISEX database is evaluated for different Signal to Noise ratio (SNR: 30 dB to -10 dB) using Aligarh Muslim University Audio Visual (AMUAV) Hindi corpus. AMUAV corpus is Hindi continuous speech high quality audio visual databases of Hindi sentences spoken by different subjects.https://acoustics.ippt.pan.pl/index.php/aa/article/view/1607Aligarh Muslim University audio visual corpusAVASRbimodalDCTDWT. |
| spellingShingle | Prashant UPADHYAYA Omar FAROOQ Musiur Raza ABIDI Priyanka VARSHNEY Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition Archives of Acoustics Aligarh Muslim University audio visual corpus AVASR bimodal DCT DWT. |
| title | Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition |
| title_full | Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition |
| title_fullStr | Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition |
| title_full_unstemmed | Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition |
| title_short | Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition |
| title_sort | comparative study of visual feature for bimodal hindi speech recognition |
| topic | Aligarh Muslim University audio visual corpus AVASR bimodal DCT DWT. |
| url | https://acoustics.ippt.pan.pl/index.php/aa/article/view/1607 |
| work_keys_str_mv | AT prashantupadhyaya comparativestudyofvisualfeatureforbimodalhindispeechrecognition AT omarfarooq comparativestudyofvisualfeatureforbimodalhindispeechrecognition AT musiurrazaabidi comparativestudyofvisualfeatureforbimodalhindispeechrecognition AT priyankavarshney comparativestudyofvisualfeatureforbimodalhindispeechrecognition |