Model reference · open weights
monsoon-whisper-medium-gigaspeech2 is an open-weight audio or speech model from typhoon-ai. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | typhoon-ai |
|---|---|
| Type | Audio & music |
| Task | Speech→text |
| Parameters (lead) | 764M |
| Runs with | transformers |
| Released | 2024-07-12 |
| Popularity | 1k downloads / month |
| Licence | Open weights |
About
Monsoon-Whisper-Medium-GigaSpeech2 is a 🇹🇭 Thai Automatic Speech Recognition (ASR) model. It is based on Whisper-Medium and fine-tuned on GigaSpeech2.
Originally developed as a scale experiment for research on emergent capabilities in ASR tasks. It performs well in the wild, including with audio sourced from YouTube and in noisy environments.
More details can be found in our Typhoon-Audio Release Blog.
By using this model, you agree to the OpenTyphoon Terms and Conditions and acknowledge the Privacy Notice: https://opentyphoon.ai/tac · https://opentyphoon.ai/privacy
from transformers import WhisperProcessor, WhisperForConditionalGeneration
import torchaudio
import torch
model_path = "scb10x/monsoon-whisper-medium-gigaspeech2"
device = "cuda"
filepath = 'audio.wav'
processor = WhisperProcessor.from_pretrained(model_path)
model = WhisperForConditionalGeneration.from_pretrained(
model_path, torch_dtype=torch.bfloat16
)
model.to(device)
model.eval()
model.config.forced_decoder_ids = processor.get_decoder_prompt_ids(
language="th", task="transcribe"
)
array, sr = torchaudio.load(filepath)
input_features = (
processor(array, sampling_rate=sr, return_tensors="pt")
.to(device)
.to(torch.bfloat16)
.input_features
)
predicted_ids = model.generate(input_features)
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
print(transcription)
| Model | WER (GS2) | WER (CV17) | CER (GS2) | CER (CV17) |
|---|---|---|---|---|
| whisper-large-v3 | 37.02 | 22.63 | 24.03 | 8.49 |
| whisper-medium | 55.64 | 43.01 | 37.55 | 16.41 |
| biodatlab-whisper-th-medium-combined | 31.00 | 14.25 | 21.20 | 5.69 |
| biodatlab-whisper-th-large-v3-combined | 29.02 | 15.72 | 19.96 | 6.32 |
| monsoon-whisper-medium-gigaspeech2 | 22.74 | 20.79 | 14.15 | 6.92 |
This model is experimental and may not always be accurate. Developers should carefully assess potential risks in the context of their specific applications.
Kunat Pipatanakul, Potsawee Manakul, Sittipong Sripaisarnmongkol, Natapong Nitarach, Warit Sirichotedumrong, Adisai Na-Thalang, Phatrasek Jirabovonvisut, Parinthapat Pengpun, Krisanapong Jirayoot, Pathomporn Chokchainant, Kasima Tharnpipitchai
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys monsoon-whisper-medium-gigaspeech2 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (monsoon-whisper-medium-gigaspeech2 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="monsoon-whisper-medium-gigaspeech2" -F file=@audio.mp3
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.