AASIST audio anti-spoofing (voice-deepfake detection) countermeasure from
"AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention
Networks"
(Jung et al., ICASSP 2022). This is the
official
AASIST
variant
(not AASIST-L), using the upstream
clovaai/aasist
ASVspoof2019 LA pretrained checkpoint. The model takes a raw speech waveform and
returns a score where
higher = more bona fide
.
This repo is self-contained for inference: the network definition is in
_net.py
and the exact wrapper used to produce the Arena scores in
aasist.py
.
Architecture
AASIST operates directly on the raw waveform: a sinc-convolution front-end and a
RawNet2-style residual encoder produce a spectro-temporal feature map, which is
modelled by heterogeneous stacking graph attention layers over spectral and
temporal sub-graphs with a learnable max/average readout, followed by a 2-class
output (bona fide vs. spoof). The Arena score is the bona-fide logit.
Reproducing the Arena scores
Inference uses a deterministic first-64600-sample window (no random crop),
matching the upstream
data_utils.pad()
used at eval. Audio is provided as
float32 mono at 16 kHz (no resampling in the wrapper).
from aasist import AASIST
m = AASIST(); m.load()
scores = m.score_batch([wav], [16000]) # higher = more bona fide
Dataset
EER %
n_trials
ASVspoof2019_LA (in-domain)
0.83
71,237
ASVspoof2021_LA
12.35
181,566
ASVspoof2021_DF
17.04
611,829
InTheWild
43.01
31,779
CD-ADD
51.05
20,786
The in-domain ASVspoof2019 LA result reproduces the paper's reported EER (~0.83%).
License
MIT (inherited from clovaai/aasist; see
LICENSE
).
Runs of SpeechAntiSpoofingBenchmarks AASIST on huggingface.co
68
Total runs
-3
24-hour runs
-26
3-day runs
-53
7-day runs
-48
30-day runs
More Information About AASIST huggingface.co Model
AASIST huggingface.co is an AI model on huggingface.co that provides AASIST's model effect (), which can be used instantly with this SpeechAntiSpoofingBenchmarks AASIST model. huggingface.co supports a free trial of the AASIST model, and also provides paid use of the AASIST. Support call AASIST model through api, including Node.js, Python, http.
AASIST huggingface.co is an online trial and call api platform, which integrates AASIST's modeling effects, including api services, and provides a free online trial of AASIST, you can try AASIST online for free by clicking the link below.
SpeechAntiSpoofingBenchmarks AASIST online free url in huggingface.co:
AASIST is an open source model from GitHub that offers a free installation service, and any user can find AASIST on GitHub to install. At the same time, huggingface.co provides the effect of AASIST install, users can directly use AASIST installed effect in huggingface.co for debugging and trial. It also supports api for free installation.