Essays about: "Speaker Diarization"
Showing result 1 - 5 of 7 essays containing the words Speaker Diarization.
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1. Analysis of speaking time and content of the various debates of the presidential campaign : Automated AI analysis of speech time and content of presidential debates based on the audio using speaker detection and topic detection
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The field of artificial intelligence (AI) has grown rapidly in recent years and its applications are becoming more widespread in various fields, including politics. In particular, presidential debates have become a crucial aspect of election campaigns and it is important to analyze the information exchanged in these debates in an objective way to let voters choose without being influenced by biased data. READ MORE
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2. Speaker diarization in challenging environments using deep networks : An evaluation of a state-of-the-art system
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Speaker diarization is the task of determining 'who spoke when' in an audio segment. Since the breakthrough of deep learning, speech technology has experienced a huge improvement in a wide range of metrics and fields, and speaker diarization is no different. READ MORE
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3. Estimating the risk of insurance fraud based on tonal analysis
University essay from Lunds universitet/Matematisk statistikAbstract : Insurance companies utilize various methods for identifying claims that are of potential fraudulent nature. With the ever progressing field of artificial intelligence and machine learning models, great interest can be found within the industry to evaluate the use of new methods that may arise as a result of new advanced models in combination with the rich data that is being gathered. READ MORE
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4. Experiments in speaker diarization using speaker vectors
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Speaker Diarization is the task of determining ‘who spoke when?’ in an audio or video recording that contains an unknown amount of speech and also an unknown number of speakers. It has emerged as an increasingly important and dedicated domain of speech research. READ MORE
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5. Speaker Diarization System for Call-center data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : To answer the question who spoke when, speaker diarization (SD) is a critical step for many speech applications in practice. The task of our project is building a MFCC-vector based speaker diarization system on top of a speaker verification system (SV), which is an existing Call-centers application to check the customer’s identity from a phone call. READ MORE