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Advancements and Challenges in Speech Recognition for Car Environments

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This course explores the complexities of speech recognition systems in automotive settings, highlighting the latest technologies and their performance metrics. It covers commercial aspects, special challenges, and solutions, including automatic SNR estimation. Techniques such as forced alignment for ASR adaptation, Microsoft SDK applications for Q&A systems, and the use of the 1200 bps MELP vocoder are discussed. Additionally, the course investigates pronunciation variation modeling in Persian, addressing out-of-vocabulary (OOV) issues and integrating Persian text-to-speech capabilities.

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Advancements and Challenges in Speech Recognition for Car Environments

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Presentation Transcript

  1. Course Projects40967Speech Processing1386-1

  2. Speech recognition in car environment: • The challenges • The latest systems and their performance • Commercial aspects • Special difficulties and solutions • Automatic SNR estimation • Forced alignment techniques for automatic adaptation of ASR systems • Microsoft SDK

  3. Question and answering systems • 1200 bps MELP vocoder • Speech search engines • Pronunciation variation modeling in Persian • OOV for continuous ASR systems

  4. Incorporating a Persian TTS in JAWS • Pitch contour specification from Persian text • Extracting stress from Persian text • Specifying speech duration from Persian text

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