Overlapped Speech Separation System (OSSS) / (Record no. 611907)

000 -LEADER
fixed length control field 01715nam a22001817a 4500
003 - CONTROL NUMBER IDENTIFIER
control field NUST
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240927092642.0
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 621.382,AZI
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Aziz, Eemaan
9 (RLIN) 126138
245 ## - TITLE STATEMENT
Title Overlapped Speech Separation System (OSSS) /
Statement of responsibility, etc. NC Eemaan Aziz, NC Hashir Rizwan, NC Ayesha Riaz, NC Usman Awan.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. MCS, NUST
Name of publisher, distributor, etc. Rawalpindi
Date of publication, distribution, etc. 2024
300 ## - PHYSICAL DESCRIPTION
Extent 84 p
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Overlapped Speech refers to speakers speaking simultaneously (i.e. speech mixture). Speech separation has long been an active research topic in the signal processing community, with its importance in a wide range of applications such as hearable devices and telecommunication systems. It is a fundamental problem for all higher-level speech processing tasks.<br/>With recent progress in deep neural networks, the separation performance has been significantly advanced by various new problems. The problem formulation of time-domain, end-to-end speech separation naturally arises to tackle the disadvantages in frequency-domain systems. We’ve used a dual path recurrent neural network for separation of mixed audios.<br/>DPRNN (Dual-Path RNN) primarily separates in the time domain for audio source separation. It leverages recurrent neural networks (RNNs) to process temporal sequences of audio data. DPRNN focuses on exploiting temporal dependencies within audio signals for effective separation. We looked into the training objectives for separating and improving the robustness under reverberant environments. This project is further analyzed and can be used as the basis for future works.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element UG EE Project
9 (RLIN) 118090
651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME
Geographic name BEE-57
9 (RLIN) 125983
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Supervisor Dr. Shibli Nisar
9 (RLIN) 112570
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Project Report

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