System Detail
speechbrain/ ecapa
ecapa
This page shows the global rank, scenario ranks, and trial-set results for this submission.
Global Position
#10/18
Public ranking position among reviewed full-core submissions.
Scenario-Macro EER
13.5461
Scenario-Macro minDCF
0.543660
Coverage
26/26
0 scenarios ranked #1
0 scenarios in top 3
Public Listing
Ranked Publicly
This full-core result is approved and included in the public ranking.
Model Provenance
Source and architecture
- Displayed name:
speechbrain/ecapa - Source: SpeechBrain
- Architecture: ECAPA-TDNN
- Submitted alias:
spkrec-ecapa-voxceleb - Created at:
2026-05-29T14:40:34.513468+00:00
Training And Links
Training data and references
- Training data: VoxCeleb1 + VoxCeleb2 training data
- Training setup: SpeechBrain ECAPA-TDNN release with attentive statistical pooling and Additive Margin Softmax loss.
- Submission mode:
full-core - Paper: ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification
Higher-Ranked Scenarios
Scenario ranks above the global position
Show 3 supporting trial sets
- VoxCeleb1-E: #2 on its trial-set ranking.
- VoxCeleb1-H: #3 on its trial-set ranking.
- VOiCES Noise/Reverb: #7 on its trial-set ranking.
Lower-Ranked Scenarios
Scenario ranks below the global position
Show 3 supporting trial sets
- GSC Short: #14 on its trial-set ranking.
- Whisper40 Whisper: #14 on its trial-set ranking.
- FFSVC 2022 Cross-Domain: #14 on its trial-set ranking.
Scenario Rankings
Full ranking across scenarios
This table shows where the model sits on each scenario, using source-balanced scenario scores and the linked trial sets as evidence.
| Scenario | Rank | Lens | Evidence | Score |
|---|---|---|---|---|
|
Noise / Reverb Robustness
How reliably the model preserves identity when room acoustics, distractor noise, and microphone placement deviate from an easier in-corpus reference condition.
|
#7/18
Competitive
|
Noise and reverberation
3.0000 EER from leader
|
5.5800
0.213320 minDCF
|
|
|
Accent / Dialect Robustness
How reliably the model tracks identity across accent and dialect mismatch.
|
#9/18
Competitive
|
Accent and dialect variation
3.0757 EER from leader
|
23.5109
0.730128 minDCF
|
|
|
Aging Robustness
How stable identity representations remain across age-derived and longitudinal recording gaps.
|
#10/18
Needs work
|
Speaker aging and time gaps
2.4831 EER from leader
|
4.5528
0.218235 minDCF
|
|
|
Distance Robustness
How much performance changes across meeting and domestic distance mismatch.
|
#10/18
Needs work
|
Distance mismatch
5.0662 EER from leader
|
14.3300
0.630306 minDCF
|
|
|
In-The-Wild Robustness
How strong the model is on unconstrained celebrity and media speech across official CN-Celeb and VoxCeleb protocols.
|
#11/18
Needs work
|
Open-domain media speech
2.8143 EER from leader
|
7.9977
0.317381 minDCF
|
|
|
Overlap Robustness
How well speaker identity survives light, mid, and heavy overlap in both meeting and domestic recordings.
|
#11/18
Needs work
|
Overlapping speakers
4.7139 EER from leader
|
14.8522
0.616222 minDCF
|
|
|
Channel / Device Robustness
How resilient the model is to device and channel mismatch.
|
#11/18
Needs work
|
Device and channel variation
10.3747 EER from leader
|
16.6850
0.817560 minDCF
|
|
|
Genre-Shift Robustness
Whether performance holds when CN-Celeb enrollment and test speech come from different source genres.
|
#12/18
Needs work
|
Source-genre variation
15.2965 EER from leader
|
29.5690
0.883898 minDCF
|
|
|
Speaking-Style Robustness
Whether the model can preserve identity across emotion-driven change, whispered speech, and noise-induced Lombard speaking style.
|
#13/18
Needs work
|
Speaking style shift
4.4366 EER from leader
|
7.2261
0.422165 minDCF
|
|
|
Short-Duration Robustness
How much performance holds up when speech evidence is limited by duration.
|
#13/18
Needs work
|
Short-duration speech
4.5620 EER from leader
|
17.0764
0.621298 minDCF
|
|
|
Cross-Lingual Robustness
How well speaker identity survives enrollment-test language mismatch.
|
#14/18
Needs work
|
Language mismatch
3.1599 EER from leader
|
7.6275
0.509746 minDCF
|
Variant Compare
Compare ECAPA-TDNN variants
Expand this section to compare checkpoints in the same architecture group by source, training data, training setup, and leaderboard result.
Show
Compare ECAPA-TDNN variants
Expand this section to compare checkpoints in the same architecture group by source, training data, training setup, and leaderboard result.
| Variant | Source | Training Data | Training Setup | Global Rank | Macro EER | Macro minDCF | Open |
|---|---|---|---|---|---|---|---|
|
speechbrain/ecapa
Current
|
SpeechBrain | VoxCeleb1 + VoxCeleb2 training data | SpeechBrain ECAPA-TDNN release with attentive statistical pooling and Additive Margin Softmax loss. |
#10
ranked
|
13.5461 | 0.543660 | Open |
| wespeaker/ecapa1024-voxceleb | WeSpeaker | VoxCeleb2 dev, 5,994 speakers | ECAPA-TDNN GLOB c1024 with ASTP pooling, 192-d embedding, ArcMargin, 150-epoch training, speed perturbation, and MUSAN/RIRS augmentation. |
#11
ranked
|
14.0835 | 0.534111 | Open |
| wespeaker/ecapa512-voxceleb | WeSpeaker | VoxCeleb2 dev, 5,994 speakers | ECAPA-TDNN GLOB c512 with ASTP pooling, 192-d embedding, ArcMargin, large-margin fine-tuning, speed perturbation, and MUSAN/RIRS augmentation. |
#13
ranked
|
14.3120 | 0.541141 | Open |
Trial-Set Results
Raw ranking by trial set
Expand this section to inspect the detailed trial-set rankings.
Show
Raw ranking by trial set
Expand this section to inspect the detailed trial-set rankings.
| Trial Set | Rank | Scenarios | Trials | Score |
|---|---|---|---|---|
|
TidyVoiceX2-ASV
TidyVoiceX2-ASV
|
#14/18
|
Cross-lingual
|
200000 |
7.6275
0.509746 minDCF
|
|
HI-MIA
HI-MIA
|
#11/18
|
Short-duration
|
660000 |
7.6850
0.369167 minDCF
|
|
GSC Short
Google Speech Commands
|
#14/18
|
Short-duration
|
220000 |
17.0600
0.777175 minDCF
|
|
GLOBE
GLOBE
|
#8/18
|
Accent/dialect
|
56848 |
25.4450
0.533282 minDCF
|
|
CN-Celeb
CN-Celeb
|
#12/18
|
In-the-wild
|
3484292 |
15.2177
0.579855 minDCF
|
|
CN-Celeb Genre
CN-Celeb
|
#12/18
|
Genre shift
|
440000 |
29.5690
0.883898 minDCF
|
|
CN-Celeb Short
CN-Celeb
|
#13/18
|
Short-duration
|
546964 |
28.7238
0.867746 minDCF
|
|
VoxCeleb1-O
VoxCeleb1
|
#10/18
|
In-the-wild
|
37611 |
0.9038
0.071152 minDCF
|
|
VoxCeleb1-E
VoxCeleb1
|
#2/18
|
In-the-wild
|
579818 |
0.4563
0.030992 minDCF
|
|
VoxCeleb1-H
VoxCeleb1
|
#3/18
|
In-the-wild
|
550894 |
0.9731
0.062575 minDCF
|
|
VoxCeleb Short
VoxCeleb1
|
#8/18
|
Short-duration
|
394724 |
14.8367
0.471104 minDCF
|
|
3D-Speaker Device
3D-Speaker
|
#11/18
|
Channel/device
|
180000 |
21.0200
0.926620 minDCF
|
|
3D-Speaker Distance
3D-Speaker
|
#10/18
|
Distance
|
175163 |
21.5753
0.911160 minDCF
|
|
3D-Speaker Dialect
3D-Speaker
|
#10/18
|
Accent/dialect
|
180000 |
21.5767
0.926973 minDCF
|
|
FFSVC 2022 Cross-Channel
FFSVC 2022
|
#14/18
|
Channel/device
|
72000 |
12.3500
0.708500 minDCF
|
|
FFSVC 2022 Cross-Domain
FFSVC 2022
|
#14/18
|
Distance
|
66546 |
12.4662
0.716863 minDCF
|
|
Whisper40 Whisper
Whisper40
|
#14/18
|
Speaking style
|
17600 |
15.6250
0.849062 minDCF
|
|
Lombard Grid Lombard
Lombard Grid
|
#9/18
|
Speaking style
|
29524 |
0.2608
0.021386 minDCF
|
|
VOiCES Noise/Reverb
VOiCES
|
#7/18
|
Noise/reverb
|
55000 |
5.5800
0.213320 minDCF
|
|
CHiME-6 Domestic Far-Field
CHiME-6
|
#7/18
|
Distance
|
36487 |
12.4299
0.530841 minDCF
|
|
CHiME-6 Overlap
CHiME-6
|
#10/18
|
Overlap
|
39600 |
18.1111
0.681778 minDCF
|
|
ESD
ESD
|
#11/18
|
Speaking style
|
437408 |
5.7925
0.396047 minDCF
|
|
AliMeeting Near/Far
AliMeeting
|
#12/18
|
Distance
|
220000 |
10.8485
0.362360 minDCF
|
|
AliMeeting Overlap
AliMeeting
|
#14/18
|
Overlap
|
165000 |
11.5933
0.550667 minDCF
|
|
VoxKnesset
VoxKnesset
|
#11/18
|
Aging
|
158312 |
6.9067
0.325019 minDCF
|
|
VoxPopuli Aging
VoxPopuli
|
#8/18
|
Aging
|
146575 |
2.1989
0.111452 minDCF
|