E-Books → The Economist Audio Edition - November 19, 2022
Published by: voska89 on 19-11-2022, 07:10 | 0
English | 2022 | MP3 | 218 MB
About The Economist
Multimedia → Heckmann Audio - u-he Dark Zebra v2.9.3
Published by: voska89 on 18-11-2022, 04:18 | 0
Heckmann Audio - u-he Dark Zebra v2.9.3 | 55.3 Mb
The Dark Zebra arose from a collaboration between Hans Zimmer and Howard Scarr. The soundset contains 400 presets-nearly all the Zebra sounds found in the The Dark Knight and The Dark Knight Rises soundtracks, and some that did not make it into those films.
E-Books → The History and Archaeology of the Bible [TTC Audio]
Published by: voska89 on 18-11-2022, 03:11 | 0
English | January 08, 2021 | ASIN: B08S1C8BDZ | MP3 | M4B | 11h 21m | 664 MB
Lecturer: Jean-Pierre Isbouts
E-Books → The Economist Audio Edition - October 29, 2022
Published by: voska89 on 18-11-2022, 02:59 | 0
English | 2022 | MP3 | 192 MB
About The Economist
E-Books → The Economist Audio Edition - October 22, 2022
Published by: voska89 on 18-11-2022, 02:59 | 0
English | 2022 | MP3 | 210 MB
About The Economist
E-Books → The Economist Audio Edition - October 15, 2022
Published by: voska89 on 18-11-2022, 02:58 | 0
English | 2022 | MP3 | 252 MB
About The Economist
E-Books → The Economist Audio Edition - November 12, 2022
Published by: voska89 on 18-11-2022, 02:58 | 0
English | 2022 | MP3 | 223 MB
About The Economist
E-Books → The Economist Audio Edition - November 05, 2022
Published by: voska89 on 18-11-2022, 02:58 | 0
English | 2022 | MP3 | 251 MB
About The Economist
E-Books → Learning How to Learn [TTC Audio]
Published by: voska89 on 18-11-2022, 01:03 | 0
English | June 09, 2022 | ASIN: B0B3F7D5YW | MP3 | M4B | 4h 21m | 237 MB
Lecturer: Tesia Marshik
E-Books → An Introduction to Audio Content Analysis Music Information Retrieval Tasks and Applications, 2nd Edition
Published by: voska89 on 17-11-2022, 05:17 | 0
English | 2022 | ISBN: 978-1119890942 | 467 pages | True PDF | 29.73 MB
An Introduction to Audio Content Analysis Enables readers to understand the algorithmic analysis of musical audio signals with AI-driven approaches
An Introduction to Audio Content Analysis serves as a comprehensive guide on audio content analysis explaining how signal processing and machine learning approaches can be utilized for the extraction of musical content from audio. It gives readers the algorithmic understanding to teach a computer to interpret music signals and thus allows for the design of tools for interacting with music. The work ties together topics from audio signal processing and machine learning, showing how to use audio content analysis to pick up musical characteristics automatically. A multitude of audio content analysis tasks related to the extraction of tonal, temporal, timbral, and intensity-related characteristics of the music signal are presented. Each task is introduced from both a musical and a technical perspective, detailing the algorithmic approach as well as providing practical guidance on implementation details and evaluation.