Model reference · open weights
TIGER-DnR is an open-weight audio or speech model from JusperLee, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
TIGER is a lightweight model for speech separation which effectively extracts key acoustic features through frequency band-split, multi-scale and full-frequency-frame modeling. 💥 News - [2025-01-23] We release the code and pre-trained model of TIGER! 🚀 - [2025-01-23] We release the TIGER model and the EchoSet dataset! 🚀 📜 Abstract In this paper, we propose a speech separation model with significantly reduced parameter size and computational cost: Time-Frequency Interleaved Gain Extraction and Reconstruction Network (TIGER). TIGER leverages prior knowledge to divide frequency bands and applies compression on frequency information. We employ a multi-scale selective attention (MSA) module to extract contextual features, while introducing a full-frequency-frame attention (F^3A) module to capture both temporal and frequency contextual information. Additionally, to more realistically evaluate the performance of speech separation models in complex acoustic environments, we introduce a novel dataset called EchoSet. This dataset includes noise and more realistic reverberation (e.g., considering object occlusions and material properties), with speech from two speakers overlapping at random proportions. Experimental results demonstrated that TIGER significantly outperformed state-of-the-art (SOTA) model TF-GridNet on the EchoSet dataset in both inference speed and separation quality, while reducing the number of parameters by 94.3% and the MACs by 95.3%. These results indicate that by utilizing frequency band-split and interleaved modeling structures, TIGER achieves a substantial reduction in parameters and computational costs while maintaining high performance. Notably, TIGER is the first speech separation model with fewer than 1 million parameters that achieves performance close to the SOTA model. 🚀 Quick Start Test with Pre-trained Model Train with EchoSet Evaluate with EchoSet 📖 Citation 📧 Contact If you have any questions, please feel free to contact us via tsinghua.kaili@gmail.com.
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | JusperLee |
|---|---|
| Type | Audio & music |
| Parameters (lead) | 4M |
| Variants | 1 |
| Released | 2025-01-22 |
| Popularity | 115k downloads / month |
| Likes | 23 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| TIGER-DnR | 4M | BF16 | ~0 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys tiger-dnr for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (tiger-dnr below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="tiger-dnr" -F file=@audio.mp3
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗