Главная
Study mode:
on
1
Intro
2
Rev Data
3
Word Error Rate
4
Organization Entity
5
Test Benchmark
6
Data Selection
7
Speech Input
8
Subword Units
9
Melscale
10
Encoder Decoder
11
Speech Recognition
12
AttentionBased ASR
13
ConnectionistTemporal Classification
14
Language Models
15
Questions
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore automatic speech recognition in this MIT 6.S191 lecture featuring Rev.com experts Miguel Jetté and Jennifer Drexler. Delve into how Rev.com combines human-in-the-loop techniques with deep learning to create a cutting-edge English speech recognition engine. Learn about word error rates, data selection, speech input processing, subword units, melscale encoding, decoder mechanisms, attention-based ASR, connectionist temporal classification, and language models. Gain insights into the latest advancements in speech recognition technology and its practical applications in the industry.

MIT 6.S191 - Automatic Speech Recognition

Alexander Amini
Add to list
0:00 / 0:00