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Approaches for Multilingual Phone Recognition in Code-switched and Non-code-switched Scenarios Using Indian Languages., , , , and . ACM Trans. Asian Low Resour. Lang. Inf. Process., 20 (4): 55:1-55:19 (2021)Phoneme State Posteriorgram Features for Speech Based Automatic Classification of Speakers in Cold and Healthy Condition., , and . INTERSPEECH, page 3462-3466. ISCA, (2017)MUCS 2021: Multilingual and Code-Switching ASR Challenges for Low Resource Indian Languages., , , , , , , , , and 10 other author(s). Interspeech, page 2446-2450. ISCA, (2021)Semi-supervised and Active-learning Scenarios: Efficient Acoustic Model Refinement for a Low Resource Indian Language., , , and . INTERSPEECH, page 1041-1045. ISCA, (2018)An ASR Corpus in Chhattisgarhi, a Low Resource Indian Language., , , , , , , , , and 8 other author(s). SPECOM (2), volume 14339 of Lecture Notes in Computer Science, page 173-181. Springer, (2023)Semi-supervised learning for acoustic model retraining: Handling speech data with noisy transcript., , , , , and . SPCOM, page 1-5. IEEE, (2020)Model Adaptation for ASR in low-resource Indian Languages., , , , , , , , , and 10 other author(s). CoRR, (2023)Multilingual and code-switching ASR challenges for low resource Indian languages., , , , , , , , , and 12 other author(s). CoRR, (2021)Gated Multi Encoders and Multitask Objectives for Dialectal Speech Recognition in Indian Languages., , , , , , , , , and 1 other author(s). ASRU, page 1-8. IEEE, (2023)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)