Command-line Clients
Contents
Command-line Clients#
Data Center
The Riva Speech Docker image contains sample command-line drivers for the Riva Speech AI services. Pull and run the container by using the following commands. The client expects that a Riva server is running with models deployed, and all command-line drivers accept an optional argument to specify the location of the server. No GPU is required to run the sample clients.
docker pull nvcr.io/nvidia/riva/riva-speech:2.18.0
docker run -it --rm nvcr.io/nvidia/riva/riva-speech:2.18.0
Embedded
The sample command-line clients are present in the Riva Speech AI server container. Refer to the Quick Start Guide for steps on how to launch the Riva Speech AI server container.
Speech Recognition#
Both binary and Python clients are included in the Docker image with options to perform ASR inference in streaming as well as offline (nonstreaming) mode.
Binary Streaming Example#
Run the ASR streaming client, where --audio_file
specifies the
audio file that is to be transcribed. Other options can be found in
riva_streaming_asr_client --help
.
Note
.wav
, .opus
, and .ogg
(Opus-encoded) containers are currently supported.
riva_streaming_asr_client --audio_file /work/wav/test/1272-135031-0001.wav
Binary Offline/Batch (nonstreaming) Example#
Run the binary ASR offline client, where --audio_file
specifies the
audio file that is to be transcribed. Other options can be found in
riva_asr_client --help
.
riva_asr_client --audio_file /work/wav/test/1272-135031-0001.wav
Python Streaming Example#
Run the Python ASR streaming client, where --input-file
specifies the
audio file that is to be transcribed. Other options can be found in the
riva_streaming_asr_client.py
script.
python riva_streaming_asr_client.py --input-file=/work/wav/test/1272-135031-0001.wav
The transcribe_mic.py
example is the preferred,
cross-platform way to interact with Riva. Additionally, using a microphone from an arbitrary remote system
running on any operating system and hardware platform is recommended.
python transcribe_mic.py --input-device <device_id>
Where the <device_id>
of your audio input device can be obtained from:
python transcribe_mic.py --list-devices
Similarly, the transcribe_file.py
example transcribes audio files in streaming mode.
Python Offline Example#
Run the Python ASR offline client, where --input-file
specifies the
audio file that is to be transcribed. Other options can be found in the
transcribe_file_offline.py
script.
python transcribe_file_offline.py --input-file=/work/wav/test/1272-135031-0001.wav
HTTP Client Offline Example#
Run the following command to transcribe an audio file with the offline ASR model using the HTTP API,
where file
specifies the audio file that is to be transcribed, and language
specifies
the language code of input audio file.
curl -s http://localhost:50000/v1/audio/transcriptions -F file="@/work/wav/test/1272-135031-0000.wav" -F language=en-US
Binary Offline Speaker Diarization Example#
Run the binary ASR offline client, where --audio_file
specifies the audio file to be diarized and --speaker_diarization
is the flag to enable diarization.
riva_asr_client --audio_file /opt/riva/wav/en-US_sample.wav --speaker_diarization=true
Python Offline Speaker Diarization Example#
Run the Python ASR offline client, where --input-file
specifies the audio file to be diarized and --speaker-diarization
is the flag to enable diarization.
python transcribe_file_offline.py --input-file /opt/riva/wav/en-US_sample.wav --speaker-diarization
Natural Language Processing#
Both binary and Python clients are included in the Docker image for supported NLP tasks.
Binary Punctuation Example#
Run the Punctuation client, where --queries
specifies the file containing
inputs to punctuate. Note that if you want to specify --output
to write output of the
punctuation model to a file, you need to also specify --parallel_requests=1
.
riva_nlp_punct --queries=/work/test_files/nlu/punctuation_input.txt
Speech Synthesis#
Binary clients are supported in the Docker image for TTS.
Binary TTS Client Example#
Run the binary TTS client, where --text
is used to specify the input text for which to
synthesize audio. The output of the client is a .wav
file, which can be specified by --audio_file
. Other options can be
found in riva_tts_client --help
.
riva_tts_client --text="I had a dream yesterday." --audio_file=/opt/riva/wav/output.wav
Binary TTS Performance Client Example#
Run the binary TTS performance client, which provides information about latency and
throughput. Options --text
specifies the input text and --text_file
specifies the file containing multiple text inputs. Other options can be found in
riva_tts_perf_client --help
.
riva_tts_perf_client --text_file=/work/test_files/tts/ljs_audio_text_test_filelist_small.txt
Python Client Examples#
The talk.py
script is an implementation of a client for performing offline and streaming (with audio being streamed
back to the client in chunks) inference.
python talk.py --stream --output-device <device_id>
where the <device_id>
of your audio output device can be obtained from:
python talk.py --list-devices
Machine Translation#
Both binary and python clients are supported in the Docker image for neural machine translation (NMT).
Binary Text Translation Example#
Retrieve the available models and language pairs
riva_nmt_t2t_client --list_models
languages {
key: "en_de_24x6"
value {
src_lang: "en"
tgt_lang: "de"
}
}
Run the binary client
riva_nmt_t2t_client --model_name=en_de_24x6 --source_language_code="en-US" --target_language_code="de-DE" --text="This will become German words." --riva_uri=0.0.0.0:50051
Where:
--source_language_code
is the source language code--target_language_code
is the target language code--text
is the text you want translated--riva_uri
is the IP address of the server--model_name
is the name of the model
To translate a .txt
file, ensure every sentence forms a new line, then run:
riva_nmt_t2t_client --source_language_code es-US --target_language_code en-US --text_file /raid/wmt_tests/wmt13-es-en.es --riva_uri=0.0.0.0:50051 --model_name mnmt_deesfr_en_transformer12x2 --batch_size=8
Where:
--text_file
is the path to the file that you want translatedbatch_size
is the size of the batch. The default is8
.
Python Client Examples#
A provided Python client implements the gRPC API.
For example, to translate the sentence Please translate this English to German. into German, run:
Retrieve the available models and language pairs
python3 /opt/riva/examples/nmt.py --list-models
languages {
key: "en_de_24x6"
value {
src_lang: "en"
tgt_lang: "de"
}
}
Run the python client
python3 /opt/riva/examples/nmt.py --source-language-code=en-US --target-language-code=de-DE --text="Please translate this English to German." --server=0.0.0.0:50051 --model-name=en_de_24x6
Where:
--source-language-code
is the source language code--target-language-code
is the target language code--text
is the text you want translated--server
is the IP address of the server--model-name
is the name of the model
To translate a .txt
file, ensure every sentence forms a new line, then run:
python3 /opt/riva/examples/nmt.py --source-language-code es-US --target-language-code en-US --text-file /raid/wmt_tests/wmt13-es-en.es --server=0.0.0.0:50051 --model-name mnmt_deesfr_en_transformer12x2 --batch-size=8
Where:
--text-file
is the path to the file that you want translatedbatch-size
is the size of the batch. The default is8
.
Speech-to-Speech Translation#
The binary client supports the Speech-to-Speech (S2S) service in Docker.
Binary Speech-to-Speech Translation Client Example#
Run the binary client.
riva_nmt_streaming_s2s_client --riva_uri=0.0.0.0:50051 --audio_file=/opt/riva/wav/es-US_sample.wav --source_language_code="es-US" --target_language_code="en-US"
Where:
--audio_file
is the input audio file--source_language_code
is the source language--target_language_code
is the target language--riva_uri
is the IP address of the server
Other parameter options can be found in riva_nmt_streaming_s2s_client --help
.
Speech-to-Text Translation#
The binary client supports the Speech-to-Translate (S2T) service in Docker.
Binary Speech-to-Text Translation Client Example#
Run the binary client.
riva_nmt_streaming_s2t_client --riva_uri=0.0.0.0:50051 --audio_file=/opt/riva/wav/en-US_sample.wav --source_language_code="en-US" --target_language_code="de-DE"
Where:
--audio_file
is the input audio file--source_language_code
is the source language--target_language_code
is the target language--riva_uri
is the IP address of the server
Other parameter options can be found in riva_nmt_streaming_s2t_client --help
.