README.md

VoiceConvAI

Voice Conversation AI Task

Task

The objective of this task is to develop a pipeline that:

Accepts an audio file recording of the conversation as input

Generates a summary of the conversation in SOAP format

Requirements

• Language of conversation - English
• Programming language - Python

Models

• QuartzNet - https://catalog.ngc.nvidia.com/orgs/nvidia/models/quartznet15x5
• PyAnnote - https://huggingface.co/pyannote/speaker-diarization-3.1 # optional
• omi-health/sum-small - https://huggingface.co/omi-health/sum-small
• LLama - https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF

Instalattion

I used the base image - nvcr.io/nvidia/pytorch:24.04-py3

apt update
apt install ffmpeg

pip install -r req.txt

System

System characteristics on which the project started and worked correctly

• ubuntu 18.04
• cuda 12.1 driver 530.41
• 2x 3090
• AMD Ryzen Threadripper 1920X 12-Core
• 128 gb Ram

Pyannote

See installation guide - https://huggingface.co/pyannote/speaker-diarization-3.1

pip install pyannote.audio

LLama

See installation guide https://github.com/ggerganov/llama.cpp

You need to download llama-2-7b-chat.Q4_K_M.gguf

git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
make

Usage

In general, you can use any audio file that is supported by ffmpeg

To run you need to enter the command in the console:

python main.py wav_path '/path/to/file' --llm True --device 'cpu'

Arguments:

• --wav_path - path to your file (optional wav)
• --llm - If True - LLama is used, if False - omi-health/sum-small is used
• --device - CPU or GPU

Results

soon

Inference time

• CUDA: soon

• CPU: soon