ReazonSpeech-NeMo-v2
| Property | Value |
|---|---|
| Parameter Count | 619M |
| License | Apache 2.0 |
| Language | Japanese |
| Research Paper | Fast Conformer Paper |
What is reazonspeech-nemo-v2?
ReazonSpeech-NeMo-v2 is an advanced automatic speech recognition (ASR) model specifically designed for Japanese language processing. Built on the ReazonSpeech v2.0 corpus, this model represents a significant advancement in long-form audio processing, capable of handling audio clips up to several hours in length.
Implementation Details
The model implements an improved Conformer architecture with several innovative features. At its core, it utilizes a subword-based RNN-T model with a total of 619M parameters. The architecture incorporates Longformer attention with a local context size of 256 and a single global token, enabling efficient processing of extended audio sequences.
- Utilizes SentencePiece unigram tokenizer with 3000 token vocabulary
- Trained for 1 million steps using AdamW optimizer
- Implements Noam annealing schedule for optimization
- Features Longformer attention mechanism for efficient processing
Core Capabilities
- Long-form Japanese audio transcription
- Efficient processing of multi-hour audio clips
- High-accuracy speech recognition with advanced attention mechanism
- Streamlined integration through reazonspeech library
Frequently Asked Questions
Q: What makes this model unique?
The model's distinctive feature is its ability to handle long-form Japanese audio using an improved Conformer architecture with Longformer attention, making it particularly efficient for processing extended audio sequences while maintaining high accuracy.
Q: What are the recommended use cases?
This model is ideal for Japanese speech transcription tasks, particularly those involving long-form content such as lectures, interviews, or extended recordings. It's particularly suitable for applications requiring high-accuracy Japanese ASR with support for multi-hour audio processing.
