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An overview of automatic speaker diarization systems
Audio diarization is the process of annotating an input audio channel with information that
attributes (possibly overlap**) temporal regions of signal energy to their specific sources …
attributes (possibly overlap**) temporal regions of signal energy to their specific sources …
Speaker segmentation and clustering
This survey focuses on two challenging speech processing topics, namely: speaker
segmentation and speaker clustering. Speaker segmentation aims at finding speaker …
segmentation and speaker clustering. Speaker segmentation aims at finding speaker …
Retrieval and browsing of spoken content
Ever-increasing computing power and connectivity bandwidth, together with falling storage
costs, are resulting in an overwhelming amount of data of various types being produced …
costs, are resulting in an overwhelming amount of data of various types being produced …
A review on speaker diarization systems and approaches
Speaker indexing or diarization is an important task in audio processing and retrieval.
Speaker diarization is the process of labeling a speech signal with labels corresponding to …
Speaker diarization is the process of labeling a speech signal with labels corresponding to …
Spoken content retrieval: A survey of techniques and technologies
Speech media, that is, digital audio and video containing spoken content, has blossomed in
recent years. Large collections are accruing on the Internet as well as in private and …
recent years. Large collections are accruing on the Internet as well as in private and …
Analysis and compensation of Lombard speech across noise type and levels with application to in-set/out-of-set speaker recognition
Speech production in the presence of noise results in the Lombard effect, which is known to
have a serious impact on speech system performance. In this study, Lombard speech …
have a serious impact on speech system performance. In this study, Lombard speech …
Advances in phone-based modeling for automatic accent classification
It is suggested that algorithms capable of estimating and characterizing accent knowledge
would provide valuable information in the development of more effective speech systems …
would provide valuable information in the development of more effective speech systems …
On Growing and Pruning Kneser–Ney Smoothed -Gram Models
N-gram models are the most widely used language models in large vocabulary continuous
speech recognition. Since the size of the model grows rapidly with respect to the model …
speech recognition. Since the size of the model grows rapidly with respect to the model …
Unsupervised accent classification for deep data fusion of accent and language information
Abstract Automatic Dialect Identification (DID) has recently gained substantial interest in the
speech processing community. Studies have shown that the variation in speech due to …
speech processing community. Studies have shown that the variation in speech due to …
Rapid yet accurate speech indexing using dynamic match lattice spotting
The support for typically out-of-vocabulary query terms such as names, acronyms, and
foreign words is an important requirement of many speech indexing applications. However …
foreign words is an important requirement of many speech indexing applications. However …