![]() ![]() Rerun bash riva_start.sh to restart the Riva Speech Skills server. If you see any errors during this step, start again from step 1.3.ġ.6. Rerun bash riva_init.sh to download and initialize the Spanish models and pipeline. Update the config.sh file: Update the language_code=("en-US") line to include the Spanish (language code "es-US") model according to the instructions above this line in the config.sh script.ġ.5. The Docker images can also be removed, however, you’ll be asked for confirmation before removal.ġ.4. This stops and removes all Riva-related containers, as well as deletes the Docker volume or directory used to store model files. Run bash riva_clean.sh to clean up previous local Riva installation. If Riva Speech Skills server is not currently running, you can skip this step.ġ.3. Run bash riva_stop.sh to shut down the running Riva Speech Skills server. You downloaded this folder in the Requirements and setup section above.ġ.2. Navigate to the Quick Start Guide folder. Start the Riva Speech Skills server, with the Spanish ASR pipeline.ġ.1. Through a series of system-wide optimizations, we’ve achieved 90 cost reduction for ChatGPT since December we’re now passing through those savings to API users. Note: The Riva Speech Skills server Quick Start Guide, that we followed in the Requirements and Setup section above for English ASR, explains how to deploy only English models by default. ChatGPT and Whisper models are now available on our API, giving developers access to cutting-edge language (not just chat) and speech-to-text capabilities. The only difference is before running inference on the Spanish audio, we need to first deploy the Spanish ASR pipeline on the Riva Speech Skills server. The requirements and setup steps for non-English ASR (in this case Spanish ASR) is the almost the same as for English ASR. Requirements and Setup for Spanish ASR: # Typical microphones have 1 audio channel. Max_alternatives - Determines the number of top alternative transcriptions to returnĮnable_automatic_punctuation - Adds a punctuation at the end of VAD (Voice Activity Detection).Īudio_channel_count - Number of audio channels. We will explore ASR for non-English languages in the next section. Other options include ( es-US, de-DE, ru-RU, zh-CN). Language_code - Language of the input audio. wav file and resampled if needed, making this parameter optional. Note that the sample rate can be detected automatically from the audio. Sample_rate_hertz - Sampling rate of the input audio in Hz. Supports ( LINEAR_PCM, FLAC, MULAW or ALAW). Let’s learn more about these parameters:Įncoding - Type of audio encoding of the input audio file. ![]() ![]() Riva ASR supports a number of options while making a transcription request to the gRPC endpoint, as shown in the previous section. Virtual Assistant (with Google Dialogflow) How to Deploy Riva at Scale on AWS with EKS The Making of the Riva Mandarin ASR Service Speech Recognition - New Language Adaptation How to deploy custom Acoustic Model (Citrinet) trained with TAO Toolkit on Riva How to Fine-Tune a Riva ASR Acoustic Model (Citrinet) with TAO Toolkit How to pretrain a Riva ASR Language Modeling (n-gram) with TAO Toolkit How to Customize Riva ASR Vocabulary and Pronunciation with Lexicon Mapping How do I boost specific words at runtime with word boosting? How to Improve Recognition of Specific Words How do I use Riva ASR APIs with out-of-the-box models? ![]()
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