toolevalxm/SpeechAI-Pro-TestRepo

SpeechAI-Pro

<div align="center"> <img src="figures/logo.png" width="60%" alt="SpeechAI-Pro" /> </div> <hr>

<div align="center" style="line-height: 1;"> <a href="LICENSE" style="margin: 2px;"> <img alt="License" src="figures/badge.png" style="display: inline-block; vertical-align: middle;"/> </a> </div>

1. Introduction

SpeechAI-Pro is a state-of-the-art speech processing model designed for multiple speech-related tasks including automatic speech recognition (ASR), speaker identification, emotion detection, and speech synthesis. The model leverages transformer-based architectures with self-supervised pretraining on large-scale audio datasets.

<p align="center"> <img width="80%" src="figures/architecture.png"> </p>

Key features of SpeechAI-Pro:

• —Multi-task learning across 10 speech processing benchmarks
• —Robust performance in noisy environments
• —Support for over 100 languages
• —Real-time inference capabilities

2. Evaluation Results

Comprehensive Benchmark Results

<div align="center">

</div>

Overall Performance Summary

SpeechAI-Pro achieves state-of-the-art results across all speech processing benchmarks.

3. Usage

from transformers import AutoModel, AutoProcessor

model = AutoModel.from_pretrained("username/SpeechAI-Pro")
processor = AutoProcessor.from_pretrained("username/SpeechAI-Pro")

# Process audio
inputs = processor(audio_array, sampling_rate=16000, return_tensors="pt")
outputs = model(**inputs)

4. Training Details

The model was trained for 80 epochs on a diverse speech corpus comprising:

• —100,000 hours of transcribed speech
• —50,000 hours of multilingual audio
• —Synthetic speech data for robustness

5. License

This model is licensed under the Apache 2.0 License.

6. Contact

For questions, please open an issue on our GitHub repository.