Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Voice Activity Detection"”.
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Neural Voice Activity Detection and its practical use
The task of producing a Voice Activity Detector (VAD) that is robust in the presence of non-stationary background noise has been an active area of research for several decades. Historically, many of the proposed VAD models have been highly heuristic in nature. More recently, however, statistical …
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Speech enhancement using multisensory cooperative computing
… modes, by suppressing redundant synaptic activity. MCC establishes a paradigm for energy-efficient, high-capacity neuromorphic computing suited to real-time audio-visual learning. Second, to address AVSE on resource-constrained edge devices and the challenges of real-world noise, a novel …
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Parkinsonian Speech and Voice Quality: Assessment and Improvement
… nearly 90% of people impaired with PD develop voice and speech disorders. Speech production impairments in PD subjects typically result in hypophonia and consequently, poor speech signal-to-noise ratio (SNR) in noisy environments and inferior speech intelligibility and quality. Assessment, …
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Energy-scalable speech recognition circuits
… (Kaldi) on the hardware platform. We investigate voice activity detection (VAD) as a wake-up mechanism and conclude that an accurate and robust algorithm is necessary to minimize system power, even if it results in larger area and power for the VAD itself. We design fixed-point digital …
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On-device mobile speech recognition
… the wireless client-server bottleneck. For the Voice Activity Detection part of this work, this thesis presents two novel algorithms used to detect speech activity within an audio signal. The first algorithm is based on the Log Linear Predictive Cepstral Coefficients Residual signal. These …
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Development of machine learning based speaker recognition system
… system that is capable of recognizing its users’ voice using advanced machine learning and digital signal processing tools. The proposed system can both validate a person’s identity (i.e. verification) and recognize it from a larger known group of people (i.e. identification). We designed the …
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Neural Time Alignment for End-to-End Automatic Speech Recognition Systems
… encoder and decoder as the input, and deal with Voice Activity Detection (VAD). Unlike the LSyncNA module, the FSyncNA module uses dynamic programming (the Viterbi algorithm) to find out the absolute word-level time alignment, hence the inference phase of FSyncNA is slower than LSyncNA. …