Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/1456
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dc.contributor.authorGoel, Arnav
dc.contributor.authorHira, Medha
dc.contributor.authorGupta, Anubha (Advisor)
dc.date.accessioned2024-05-13T13:46:51Z
dc.date.available2024-05-13T13:46:51Z
dc.date.issued2023-11-29
dc.identifier.urihttp://repository.iiitd.edu.in/xmlui/handle/123456789/1456
dc.description.abstractWe benchmark various Speech-to-Text (STT) and Text-to-Speech (TTS) models and performed an extensive literature review on downstream tasks such as Automatic Speech Recognition (ASR), Speech Emotion Recognition, Speaker Identification and Prosody Transfer. This led us to understanding the paradigms existing in the domain of audio processing and enabled us to work on speech processing and synthesis tasks. We prepared a novel multilingual speech-tospeech system with translation using State-of-the-Art ASR, TTS and Voice Conversion models. This allowed us to experiment with speaker embedding conditioning in TTS systems and explore posterior and prior conditions. We present the results in this report.en_US
dc.language.isoen_USen_US
dc.publisherIIIT-Delhien_US
dc.subjectAutomatic Speech Recognitionen_US
dc.subjectMultilingualen_US
dc.subjectSpeechen_US
dc.subjectSpeaker Embeddingsen_US
dc.subjectTextto- Speechen_US
dc.titleImproving speech to speech conversion with incorporation of speaker tonalityen_US
dc.typeOtheren_US
Appears in Collections:Year-2023

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BTP_Report_2021519 - Arnav Goel.pdf
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Medha_Report1 - Medha Hira.pdf
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