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.
Results
Showing 1 to 18 of 18 for “"Keyword Spotting"”.
-
Algorithms and low power hardware for keyword spotting
Keyword spotting (KWS) is widely used in mobile devices to provide hands-free interface. It continuously listens to all sound signals, detects specific keywords and triggers the downstream system. The key design target of a KWS system is to achieve high classification accuracy of specified keywords …
-
Morphological segmentation : an unsupervised method and application to Keyword Spotting
… segmentation on the speech recognition task of Keyword Spotting (KWS). Despite potential benefits, state-of-the-art KWS systems do not use morphological information. In this thesis, we augment a KWS system with sub-word units derived by multiple segmentation algorithms including supervised and …
-
Unsupervised spoken keyword spotting and learning of acoustically meaningful units
The problem of keyword spotting in audio data has been explored for many years. Typically researchers use supervised methods to train statistical models to detect keyword instances. However, such supervised methods require large quantities of annotated data that is unlikely to be available for the …
-
A study on out-of-vocabulary word modelling for a segment-based keyword spotting system
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
-
DESIGN OF A KEYWORD SPOTTING SYSTEM USING MODIFIED CROSS-CORRELATION IN THE TIME AND THE MFCC DOMAIN
Abstract A Keyword Spotting System (KWS) is a system that recognizes predefined keywords in spoken utterances or written documents. The objective is to obtain the highest possible keyword detection rate without increasing the number of false detections in a system. The common approach to keyword …
-
A Novel Approach for Continuous Speech Tracking and Dynamic Time Warping. Adaptive Framing Based Continuous Speech Similarity Measure and Dynamic Time Warping using Kalman Filter and Dynamic State Model
… new frame size for the next step. In addition, a keyword spotting approach is proposed by introducing wavelet decomposition based dynamic noise filter and combination of beliefs. The Dempster’s theory of belief combination is deployed for the first time in relation to keyword spotting task. …
-
Acoustic event, spoken keyword and emotional outburst detection
… on the speech acoustic events and the spoken keyword spotting task for speech. It presents a phonetic keyword spotter as a lightweight alternative to full speech recognition (3x faster, with comparable detection rates and that addresses automatic speech recognition problems). It also explores …
-
Detección de estados de ánimo mediante sentiment analysis en hispanohablantes
… by these users in text format. It was used the Keyword Spotting Technique (KST) for text treatment, and Sentiment Analysis based on only Natural Language Processing (NLP) concepts for text analysis. A mobile application with chatbot interface and a bot that invites the user to give details about …
-
Subword-based approaches for spoken document retrieval
… as an alternative to words generated by either keyword spotting or continuous speech recognition. Our investigation is motivated by the observation that word-based retrieval approaches face the problem of either having to know the keywords to search for [\em a priori], or requiring a very large …
-
Discriminative and adaptive training for robust speech recognition and understanding
… training objectives are proposed for keyword spotting and topic classification: (1) To accurately recognize the semantically important keywords, the non-uniform error cost minimum classification error training of deep neural network (DNN) and bi-directional long short-term memory …
-
Multilingual techniques for low resource automatic speech recognition
… a universal ASR framework for transcription and keyword spotting (KWS) tasks that work on a variety of languages. We investigate methods to deal with the need of a pronunciation dictionary by using a Pronunciation Mixture Model that can learn from existing lexicons and acoustic data to generate …
-
Efficient Algorithms and Systems for Tiny Deep Learning
… enables various real-world applications (e.g., keyword spotting, anomaly detection). However, deploying deep learning models to MCUs is challenging due to the limited memory size: the memory of microcontrollers is 2-3 orders of magnitude smaller even than mobile phones. In this thesis, we study …
-
Optimizing Neural Networks for Embedded Edge-Processing Platforms.
… several design parameters, referring to a Keyword Spotting task targeting a commercial micro-controller for its evaluation. We provide a fast exploration strategy, requiring around 30 hours and resulting in state-of-the-art accuracy within the defined storage constraints. We further …
-
Efficient and Collaborative Methods for Distributed Machine Learning
… community of shared interest. We apply SemiFL to Keyword Spotting (KWS), a technique widely used in virtual assistants. Numerical experiments demonstrate that one can train models from the scratch, or transfer from pre-trained models in order to leverage heterogeneous unlabeled on-device data, …
-
Neural Enhancement Strategies for Robust Speech Processing
… dataset, considering intent classification, keyword spotting, and speech recognition tasks respectively. Results show that enhancing the speech em-bedding is a viable and computationally effective approach, and provide insights about the most promising training approaches.
-
Attention-Based Encoder-Decoder Models for Speech Processing
… tasks, including semi-supervised training, keyword spotting and dialogue systems. As the second contribution of this thesis, effective confidence estimators for AED-based ASR systems are proposed. The Confidence Estimation Module (CEM) is a lightweight simple add-on neural network that takes …
-
Robust and efficient neural networks: Algorithms, architectures, and circuits
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
-
Audio computing in the wild: frameworks for big data and small computers
… using the hash codes works well for some keyword spotting tasks. From the fact that some landmark hashes (e.g. local maxima from non-maximum suppression on the magnitudes of a mel-scaled spectrogram) can also robustly represent the time-frequency domain signal efficiently, a matrix …