wav2letter | Facebook AI Research 's Automatic Speech Recognition Toolkit | Speech library

 by   facebookresearch Python Version: v0.1 License: Non-SPDX

kandi X-RAY | wav2letter Summary

kandi X-RAY | wav2letter Summary

wav2letter is a Python library typically used in Artificial Intelligence, Speech, Deep Learning, Pytorch applications. wav2letter has no bugs, it has no vulnerabilities and it has medium support. However wav2letter build file is not available and it has a Non-SPDX License. You can download it from GitHub.

wav2letter++ is a highly efficient end-to-end automatic speech recognition (ASR) toolkit written entirely in C++, leveraging ArrayFire and flashlight. The toolkit started from models predicting letters directly from the raw waveform, and now evolved as an all-purpose end-to-end ASR research toolkit, supporting a wide range of models and learning techniques. It also embarks a very efficient modular beam-search decoder, for both structured learning (CTC, ASG) and seq2seq approaches. Important disclaimer: as a number of models from this repository could be used for other modalities, we moved most of the code to flashlight.

            kandi-support Support

              wav2letter has a medium active ecosystem.
              It has 5531 star(s) with 932 fork(s). There are 249 watchers for this library.
              It had no major release in the last 12 months.
              There are 94 open issues and 754 have been closed. On average issues are closed in 113 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of wav2letter is v0.1

            kandi-Quality Quality

              wav2letter has 0 bugs and 0 code smells.

            kandi-Security Security

              wav2letter has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              wav2letter code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              wav2letter has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              wav2letter releases are available to install and integrate.
              wav2letter has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions, examples and code snippets are available.

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            wav2letter Key Features

            No Key Features are available at this moment for wav2letter.

            wav2letter Examples and Code Snippets

            Pythondot img1Lines of Code : 21dot img1no licencesLicense : No License
            copy iconCopy
            # download the pretrained model weights for English and Russian
            wget https://github.com/vadimkantorov/inferspeech/releases/download/pretrained/w2l_plus_large_mp.h5 # English, Wav2Letter
            wget https://github.com/vadimkantorov/inferspeech/releases/downl  
            Browser demo with TensorFlow.js (work in progress)
            Pythondot img2Lines of Code : 8dot img2no licencesLicense : No License
            copy iconCopy
            # download and extract the exported tfjs model
            wget https://github.com/vadimkantorov/inferspeech/releases/download/pretrained/w2l_plus_large_mp.tfjs.tar.gz
            tar -xf w2l_plus_large_mp.tfjs.tar.gz
            # serve the tfjs model and demo.html file
            python3 -m ht  
            wav2vec,Alternative install
            Pythondot img3Lines of Code : 4dot img3License : Permissive (MIT)
            copy iconCopy
            docker build -t wav2vec2 -f wav2letter.Dockerfile .
            docker run -d -it --rm -v $PWD/data:/root/data --name w2v2 wav2vec2
            docker exec -it w2v2 bash
            python examples/wav2vec/recognize.py --wav_path /root/data/temp.wav --w2v_path /root/data/wav2vec_small_  

            Community Discussions

            Trending Discussions on wav2letter


            Using C++ Libraries on Linux
            Asked 2021-Dec-22 at 04:31

            I'm trying to follow along here to use a speech recognition model. The model is in C++, and almost all of my experience is in Python.

            I installed a virtual machine running Ubuntu, and still the installation procedure was failing for me. I decided to simply try to compile the model so that I could call it in a Python script, as seen at the bottom of the linked page.

            I'm trying to use g++ to compile the .cpp model, but I keep getting an error saying that a library that I have installed is not found:



            Answered 2021-Dec-22 at 04:31

            You've installed only the runtime libraries. You also have to install the development version (e.g. header files), most likely called something like cereal-devel or so.

            Alan Birtles provided a link to the development packages in the comments section above.


            Source https://stackoverflow.com/questions/70440025

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install wav2letter

            First, isntall flashlight with all its dependencies. Then. If flashlight or ArrayFire are installed in nonstandard paths via CMAKE_INSTALL_PREFIX, they can be found by passing -Dflashlight_DIR=[PREFIX]/usr/share/flashlight/cmake/ -DArrayFire_DIR=[PREFIX]/usr/share/ArrayFire/cmake when running cmake.


            See the CONTRIBUTING file for how to help out.
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