Sequence Modeling with CTC
A visual guide to Connectionist Temporal Classification, an algorithm used to train deep neural networks in speech recognition, handwriting recognition and other sequence problems.
Sequence Modeling with CTC Sequence Modeling With CTC A visual guide to Connectionist Temporal Classification, an algorithm used to train deep neural networks in speech recognition, handwriting recognition and other sequence problems. How CTC collapsing works For an input, like speech Predict a sequence of tokens Use return to input a blank ( ϵ ) (\epsilon) ( ϵ ) Merge repeats, drop ϵ \epsilon ϵ Final output Authors Affiliations Awni Hannun Stanford University Published Nov. 27, 2017 DOI 10.23915/distill.00008 Introduction Consider speech recognition. We have a dataset of audio clips and corre
saved by
related reading
- Connectionist temporal classification - Wikipediaen.wikipedia.org
- transformer_attention.pdfarxiv.org
- Deep Knowledge Tracingstanford.edu
- Recurrent Neural Networks Tutorial, Part 1 – Introduction to RNNs · Denny's Blogdennybritz.com
- The Unreasonable Effectiveness of Recurrent Neural Networkskarpathy.github.io
- Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention) – Jay Alammar – Visualizing machine learning one concept at a time.jalammar.github.io
- Circuit Tracing: Revealing Computational Graphs in Language Modelstransformer-circuits.pub
- The Annotated Transformernlp.seas.harvard.edu
- Seq2seq and Attentionlena-voita.github.io
- The Annotated Transformernlp.seas.harvard.edu
- [2111.00396] Efficiently Modeling Long Sequences with Structured State Spacesarxiv.org
- Audio Deep Learning Made Simple: Automatic Speech Recognition (ASR), How it Works | Towards Data Sciencetowardsdatascience.com