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An Investigation of Indian Native Language Phonemic Influences on L2 English Pronunciations.

, , , , and . INTERSPEECH, page 2608-2612. ISCA, (2023)

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A comparative study on the effect of different codecs on speech recognition accuracy using various acoustic modeling techniques., , , , , , and . NCC, page 1-6. IEEE, (2017)Concatenative Articulatory Video Synthesis Using Real-Time MRI Data for Spoken Language Training., , and . ICASSP, page 4999-5003. IEEE, (2018)Can the decoded text from automatic speech recognition effectively detect spoken grammar errors?, , , , and . SLaTE, page 41-45. ISCA, (2023)Low Resource Automatic Intonation Classification Using Gated Recurrent Unit (GRU) Networks Pre-Trained with Synthesized Pitch Patterns., , and . INTERSPEECH, page 959-963. ISCA, (2019)ASR Inspired Syllable Stress Detection for Pronunciation Evaluation Without Using a Supervised Classifier and Syllable Level Features., , and . INTERSPEECH, page 924-928. ISCA, (2019)IE-CPS Lexicon: An Automatic Speech Recognition Oriented Indian-English Pronunciation Dictionary., , , , and . ICON, page 195-204. NLP Association of India (NLPAI), (2021)A Comparison of Learned Representations with Jointly Optimized VAE and DNN for Syllable Stress Detection., , and . SPECOM (2), volume 14339 of Lecture Notes in Computer Science, page 322-334. Springer, (2023)Automatic syllable stress detection under non-parallel label and data condition., and . Speech Commun., (2022)SPIRE-SST: An Automatic Web-based Self-learning Tool for Syllable Stress Tutoring (SST) to the Second Language Learners., , , and . INTERSPEECH, page 2390-2391. ISCA, (2018)Noise Robust Pitch Stylization Using Minimum Mean Absolute Error Criterion., and . Interspeech, page 1174-1178. ISCA, (2021)