Enhance input speech recorded with low-quality microphones in noisy or reverberant environments, producing studio-quality speech.
Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.
$ docker login nvcr.io
Username: $oauthtoken
Password: <PASTE_API_KEY_HERE>
NVIDIA Studio Voice NIM uses gRPC APIs for inferencing requests.
A NGC API KEY is required to download the appropriate models and resources when starting the NIM.
If you are not familiar with how to create the NGC_API_KEY environment variable, the simplest way is to export it in your terminal:
export NGC_API_KEY=<PASTE_API_KEY_HERE>
Run one of the following commands to make the key available at startup:
# If using bash
echo "export NGC_API_KEY=<value>" >> ~/.bashrc
# If using zsh
echo "export NGC_API_KEY=<value>" >> ~/.zshrc
Other, more secure options include saving the value in a file, so that you can retrieve with cat $NGC_API_KEY_FILE, or using a password manager.
The following commands launch the Studio Voice NIM container with the gRPC service. Find reference to runtime parameters for the container here.
Ensure you use the appropriate NIM_MODEL_PROFILE for your GPU. For more information about NIM_MODEL_PROFILE, refer to the the NIM Model Profile Table.
Please note, the flag --gpus all is used to assign all available GPUs to the docker container. This fails on multiple GPU unless all GPUs are same. To assign specific GPU to the docker container (in case of different multiple GPUs available in your machine) use --gpus '"device=0,1,2..."'
docker run -it --rm --name=studio-voice-nim \
--runtime=nvidia \
--gpus all \
--shm-size=8GB \
-e NGC_API_KEY=$NGC_API_KEY \
-e NIM_MODEL_PROFILE=<nim_model_profile> \
-e STREAMING=true \
-p 8000:8000 \
-p 8001:8001 \
nvcr.io/nim/nvidia/studio-voice:latest
docker run -it --rm --name=studio-voice-nim \
--runtime=nvidia \
--gpus all \
--shm-size=8GB \
-e NGC_API_KEY=$NGC_API_KEY \
-e NIM_MODEL_PROFILE=<nim_model_profile> \
-e FILE_SIZE_LIMIT=36700160 \
-e STREAMING=false \
-p 8000:8000 \
-p 8001:8001 \
nvcr.io/nim/nvidia/studio-voice:latest
If the command runs successfully, you will get an output ending similar to the following:
I1126 09:22:21.048202 31 grpc_server.cc:2558] "Started GRPCInferenceService at 127.0.0.1:9001"
I1126 09:22:21.048377 31 http_server.cc:4704] "Started HTTPService at 127.0.0.1:9000"
I1126 09:22:21.089295 31 http_server.cc:362] "Started Metrics Service at 127.0.0.1:9002"
[INFO AI4M BASE LOGGER 2026-03-06 06:54:09.052 PID:235] Listening to 0.0.0.0:8001
By default Studio Voice gRPC service is hosted on port 8001. You will have to use this port for inferencing requests.
We have provided a sample client script file in our GitHub repo. The script could be used to invoke the Docker container using the following instructions.
Download the Studio Voice Python client code by cloning the NIM gRPC Client Repository:
git clone https://github.com/NVIDIA-Maxine/nim-clients.git
cd nim-clients/studio-voice
Install the dependencies for the NVIDIA Studio Voice Python client:
sudo apt-get install python3-pip
pip install -r requirements.txt
Go to scripts directory
cd scripts
Ensure the client mode matches the NIM's STREAMING mode set in Step 2.
Run the command to send gRPC request (transactional mode i.e. STREAMING=false):
python studio_voice.py --target <target_ip:port> --input <input_file_path> --output <output_file_path>
For streaming mode:
python studio_voice.py --target <target_ip:port> --input <input_file_path> --output <output_file_path> --streaming --model-type 48k-hq
When using --streaming mode, ensure the selected --model-type (48k-hq, 48k-ll, or 16k-hq) aligns with the NIM_MODEL_PROFILE Model Type configuration to maintain compatibility .
To view details of command line arguments run this command
python studio_voice.py -h
You will get a response similar to the following.
usage: studio_voice.py [-h] [--ssl-mode {MTLS,TLS}] [--ssl-key SSL_KEY] [--ssl-cert SSL_CERT] [--ssl-root-cert SSL_ROOT_CERT] [--target TARGET]
[--input INPUT] [--output OUTPUT] [--api-key API_KEY] [--function-id FUNCTION_ID] [--streaming] [--model-type {48k-hq,48k-ll,16k-hq}]
Process wav audio files using gRPC and apply studio-voice.
options:
-h, --help show this help message and exit
--preview-mode Flag to send request to preview NVCF server on https://build.nvidia.com/nvidia/studiovoice/api.
--ssl-mode {MTLS,TLS}
Flag to set SSL mode, default is None
--ssl-key SSL_KEY The path to ssl private key.
--ssl-cert SSL_CERT The path to ssl certificate chain.
--ssl-root-cert SSL_ROOT_CERT
The path to ssl root certificate.
--target TARGET IP:port of gRPC service, when hosted locally. Use grpc.nvcf.nvidia.com:443 when hosted on NVCF.
--input INPUT The path to the input audio file.
--output OUTPUT The path for the output audio file.
--api-key API_KEY NGC API key required for authentication, utilized when using TRY API ignored otherwise
--function-id FUNCTION_ID
NVCF function ID for the service, utilized when using TRY API ignored otherwise
--streaming Flag to enable grpc streaming mode.
--model-type {48k-hq,48k-ll,16k-hq}
Studio Voice model type, default is 48k-hq.
For more details on getting started with this NIM including configuring using parameters, visit the NVIDIA Studio Voice NIM Docs.