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@google-cloud/speech
Advanced tools
The Cloud Speech API enables easy integration of Google speech recognition technologies into developer applications. Send audio and receive a text transcription from the Cloud Speech API service.
Before running the samples, make sure you've followed the steps in the Before you begin section of the client library's README.
View the source code.
Usage: node recognize.js --help
recognize.js <command>
Commands:
recognize.js sync <filename> Detects speech in a local audio file.
recognize.js sync-gcs <gcsUri> Detects speech in an audio file located in a Google Cloud Storage bucket.
recognize.js sync-words <filename> Detects speech in a local audio file with word time offset.
recognize.js async <filename> Creates a job to detect speech in a local audio file, and waits for the job to
complete.
recognize.js async-gcs <gcsUri> Creates a job to detect speech in an audio file located in a Google Cloud
Storage bucket, and waits for the job to complete.
recognize.js async-gcs-words <gcsUri> Creates a job to detect speech with word time offset in an audio file located
in a Google Cloud Storage bucket, and waits for the job to complete.
recognize.js stream <filename> Detects speech in a local audio file by streaming it to the Speech API.
recognize.js listen Detects speech in a microphone input stream. This command requires that you
have SoX installed and available in your $PATH. See
https://www.npmjs.com/package/node-record-lpcm16#dependencies
Options:
--version Show version number [boolean]
--encoding, -e [string] [default: "LINEAR16"]
--sampleRateHertz, -r [number] [default: 16000]
--languageCode, -l [string] [default: "en-US"]
--help Show help [boolean]
Examples:
node recognize.js sync ./resources/audio.raw -e LINEAR16 -r 16000
node recognize.js async-gcs gs://gcs-test-data/vr.flac -e FLAC -r 16000
node recognize.js stream ./resources/audio.raw -e LINEAR16 -r 16000
node recognize.js listen
For more information, see https://cloud.google.com/speech/docs
View the source code.
Usage: node recognize.v1p1beta1.js --help
recognize.v1p1beta1.js <command>
Commands:
recognize.v1p1beta1.js sync-model <filename> <model> Detects speech in a local audio file using provided model.
recognize.v1p1beta1.js sync-model-gcs <gcsUri> <model> Detects speech in an audio file located in a Google Cloud
Storage bucket using provided model.
Options:
--version Show version number [boolean]
--encoding, -e [string] [default: "LINEAR16"]
--sampleRateHertz, -r [number] [default: 16000]
--languageCode, -l [string] [default: "en-US"]
--help Show help [boolean]
Examples:
node recognize.v1p1beta1.js sync-model ./resources/Google_Gnome.wav video -e LINEAR16 -r 16000
node recognize.v1p1beta1.js sync-model-gcs gs://gcs-test-data/Google_Gnome.wav phone_call -e FLAC -r 16000
For more information, see https://cloud.google.com/speech/docs
View the source code.
Usage: node betaFeatures.js --help
betaFeatures.js <command>
Commands:
betaFeatures.js sync-model <filename> <model> Detects speech in a local audio file using provided model.
betaFeatures.js sync-model-gcs <gcsUri> <model> Detects speech in an audio file located in a Google Cloud
Storage bucket using provided model.
Options:
--version Show version number [boolean]
--encoding, -e [string] [default: "LINEAR16"]
--sampleRateHertz, -r [number] [default: 16000]
--languageCode, -l [string] [default: "en-US"]
--help Show help [boolean]
Examples:
node betaFeatures.js sync-model ./resources/Google_Gnome.wav video -e LINEAR16 -r 16000
node betaFeatures.js sync-model-gcs gs://gcs-test-data/Google_Gnome.wav phone_call -e FLAC -r 16000
For more information, see https://cloud.google.com/speech/docs
FAQs
Cloud Speech Client Library for Node.js
The npm package @google-cloud/speech receives a total of 44,269 weekly downloads. As such, @google-cloud/speech popularity was classified as popular.
We found that @google-cloud/speech demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
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