Print Email Facebook Twitter How Reduction in Sample Frequency Hinders the Detection of Words Title How Reduction in Sample Frequency Hinders the Detection of Words Author Alonso Arenaza, Lucia (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Hung, H.S. (mentor) Vargas Quiros, J.D. (mentor) Raman, C.A. (mentor) Baaijens, J.A. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2022-06-24 Abstract Living in a world where every single electronic device is online and interconnected, privacy is a growing concern. Finding the threshold where audio is unintelligible to transcription software is crucial when everything that we say can be recorded. Even if Automated Speech Recognition (ASR) is used in tools, such as Siri or Alexa, designed to ease daily tasks, it could also be used in malicious manners. ASR technology has not been around for too long and like any other new piece of technology, it still has many aspects that have not been looked into and are unknown to the public. This research paper addresses this knowledge gap by examining how sample frequency reduction affects word detection using current well-known transcription software technology such as Google’s speech recognition software and Kaldi’s toolkit. The behavior and performance of these two software pieces have been analyzed for different sample frequencies in the range from 300Hz to 44,1kHz. To reference this document use: http://resolver.tudelft.nl/uuid:15e23376-b68c-4029-869f-573efe4e92fc Part of collection Student theses Document type bachelor thesis Rights © 2022 Lucia Alonso Arenaza Files PDF Low_Frequency_Detection_W ... _Final.pdf 2.45 MB Close viewer /islandora/object/uuid:15e23376-b68c-4029-869f-573efe4e92fc/datastream/OBJ/view