g2p-seq2seq | G2P with Tensorflow | Machine Learning library
kandi X-RAY | g2p-seq2seq Summary
kandi X-RAY | g2p-seq2seq Summary
G2P with Tensorflow
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Top functions reviewed by kandi - BETA
- Create training data files
- Collects pronunciations from a source file
- Split a line into source and target
- Save a dictionary of pronunciations
- Freeze the model
- Evaluate the problem
- Performs decoding from a file
- Calculates the accuracy of the input file
- Performs decoding of the graph
- Run an op
- Loads the vocab
- Build a vocabulary
- Save the vocab to a file
- Runs the language model
- Prepare an interactive prediction
- Decode a single word
- Implements the interactive input function
- Creates an experiment function
- Create an experiment
- Create an experiment function
- Add problem hparams to hparams
- Runs the decodes function
- Trains the model
- Context manager for profiling
- Execute the given experiment
g2p-seq2seq Key Features
g2p-seq2seq Examples and Code Snippets
Lines of Code : 6License : Strong Copyleft (CC BY-SA 4.0)
Copypip3 -V
echo $PATH
g2p-seq2seq --version
import subprocess
open("Edited.py", "w").write("Thing To Write")
A = subprocess.Popen('Command you want to call', shell = True, stdout = subprocess.PIPE, stderr = subprocess.PIPE)
print(A.communicate())
Community Discussions
Trending Discussions on g2p-seq2seq
QUESTION
mac OS I am trying to use cmu dictionary for speech recognition. Steps I took:
...ANSWER
Answered 2019-Feb-04 at 01:24What Oluwafemi Sule says in comment is right.
QUESTION
The Carnegie Mellon University pronouncing dictionary allows to get phonemes from words. I did some research on the Internet and it appears that there are some extensions as the LOGIOS Lexicon Tool which derives the phonemes for arbitrary words that might not be included in the original CMU dictionary (http://www.speech.cs.cmu.edu/tools/lextool.html). The same can be obtained by using a neural network model (https://github.com/cmusphinx/g2p-seq2seq), so that basically for each word we can get the corresponding phonemes.
But is the process reversible for every word? Obviously for words already contained in the CMU dictionary the reversing is unnecessary since the word is attached to the corresponding phonemes. But how can I get the word from arbitrary phonemes? Is that a tool for that (possibly in Python) or should I implement the reverse by myself maybe looking at the source code doing the word-to-phoneme parsing and trying to revert it (if possible)?
...ANSWER
Answered 2018-Jun-12 at 00:40The most natural way is to train some seq2seq neural network model to perform phoneme to grapheme conversion.
g2p-seq2seq used to support phoneme to grapheme mode, see github issue, but this feature was lost in recent upgrade. It would be nice to bring it back.
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