USE
Introduction
This is the demo page of our RE-USE paper.
Examples of Non-blind test set of the URGENT 2025 Challenge:
Note:
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We provide examples for multiple languages.
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The difference between Early Reflected and Shifted Anechoic speech training targets is noticeable only when the input noisy speech contains reverberation.
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The effect of the GAN correction is typically audible only under severe degradations (e.g., low SNR, packet loss, bandwidth extension, etc.).
Example1:
Noisy (noise, bandwidth extension, clipping, reverb):
Early-reflected:
Early-reflected + GAN:
Shifted anechoic clean:
Shifted anechoic clean + GAN:
Example2:
Noisy (noise, codec, reverb):
Early-reflected:
Early-reflected + GAN:
Shifted anechoic clean:
Shifted anechoic clean + GAN:
Example3:
Noisy (noise, packet loss, reverb):
Early-reflected:
Early-reflected + GAN:
Shifted anechoic clean:
Shifted anechoic clean + GAN:
Example4:
Noisy (noise, packet loss, clipping, reverb):
Early-reflected:
Early-reflected + GAN:
Shifted anechoic clean:
Shifted anechoic clean + GAN:
Examples of our speech enhancement model applied to real noisy speech:
Example 1: Jensen’s speech
Original input (noisy, highly-reverb, bandwidth-limitation (16kHz)):
Enhanced:
Enhanced and bandwidth extension to 32k:
Example 2: Einstein’s speech
transcript: Large parts of the world are faced with starvation, while others are living in abundance.
Original input (noisy, clipping, mp3 artifact, bandwidth-limitation (8kHz)):
Enhanced:
Enhanced and bandwidth extension to 16k:
Example 3: Apollo 11 astronaut Neil Armstrong gives his classic confirmation of the first footsteps on the moon
transcript: One small step for (a) man, one giant leap for mankind.
Original input (noisy, bandwidth-limitation):
Enhanced and bandwidth extension to 16k:
Example 4: Harry Potter and the Philosopher’s Stone (2001)
Original input (noisy (music), bandwidth-limitation (16kHz)):
Enhanced:
Enhanced and bandwidth extension to 32k:
Example 5: Airport announcements
Original input (noisy, highly-reverb, multi-lingual, TTS speech):
Enhanced:
The overall ranking table for the non-blind test set of the URGENT 2025 Challenge (considering only the Early Reflected learning target for consistency):
| Team | DNSMOS | NISQA | UTMOS | PESQ | ESTOI | SDR | MCD | LSD | SpeechBERTScore | LPS | SpkSim | CAcc (%) | Overall ranking score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Bobbsun | 3.01 (8) | 3.41 (6) | 2.4 (3) | 2.95 (1) | 0.86 (1) | 14.33 (1) | 3.01 (4) | 2.83 (5) | 0.91 (1) | 0.86 (1) | 0.85 (1) | 88.92 (1) | 2.516 |
| Our Early reflected + GAN correction | 3.04 (5) | 3.53 (3) | 2.3 (6) | 2.78 (4) | 0.84 (4) | 12.25 (5) | 2.97 (3) | 2.75 (4) | 0.9 (2) | 0.84 (3) | 0.85 (1) | 88.13 (2) | 3.166 |
| rc | 3.01 (8) | 3.21 (9) | 2.3 (6) | 2.79 (3) | 0.85 (2) | 13.11 (2) | 2.93 (2) | 2.94 (8) | 0.9 (2) | 0.85 (2) | 0.84 (3) | 88.05 (3) | 4.016 |
| Our Early reflected | 3.06 (4) | 3.23 (8) | 2.26 (8) | 2.81 (2) | 0.85 (2) | 12.28 (4) | 2.87 (1) | 2.66 (1) | 0.9 (2) | 0.84 (3) | 0.82 (5) | 87.62 (5) | 4.041 |
| Xiaobin | 3.0 (10) | 3.45 (4) | 2.31 (5) | 2.74 (5) | 0.84 (4) | 13.06 (3) | 3.3 (6) | 3.08 (11) | 0.89 (5) | 0.84 (3) | 0.83 (4) | 87.94 (4) | 5.033 |
| subatomicseer | 3.02 (6) | 3.28 (7) | 2.34 (4) | 2.63 (7) | 0.82 (6) | 12.18 (6) | 3.9 (12) | 3.06 (10) | 0.88 (7) | 0.82 (6) | 0.82 (5) | 86.15 (7) | 6.591 |
| poisonous | 3.02 (6) | 3.42 (5) | 2.26 (8) | 2.72 (6) | 0.82 (6) | 11.93 (8) | 3.36 (9) | 2.69 (2) | 0.89 (5) | 0.81 (8) | 0.8 (8) | 85.65 (8) | 6.758 |
| byti.shsy | 2.96 (12) | 3.15 (10) | 2.18 (10) | 2.44 (9) | 0.82 (6) | 12.09 (7) | 3.28 (5) | 3.27 (12) | 0.88 (7) | 0.82 (6) | 0.82 (5) | 86.46 (6) | 7.616 |
| Lam-Fung | 2.97 (11) | 2.95 (12) | 2.11 (15) | 2.43 (10) | 0.8 (9) | 11.37 (9) | 3.32 (7) | 2.84 (6) | 0.86 (10) | 0.79 (9) | 0.8 (8) | 84.93 (10) | 9.8416 |
| urgent | 2.94 (13) | 2.89 (13) | 2.11 (15) | 2.43 (10) | 0.8 (9) | 11.29 (10) | 3.32 (7) | 2.85 (7) | 0.86 (10) | 0.79 (9) | 0.8 (8) | 84.96 (9) | 10.066 |
| cobalamin | 3.11 (3) | 2.7 (17) | 2.15 (11) | 2.22 (14) | 0.71 (16) | 6.22 (16) | 3.44 (10) | 2.72 (3) | 0.87 (9) | 0.79 (9) | 0.78 (12) | 83.73 (11) | 10.658 |
| alindborg | 3.28 (1) | 3.96 (2) | 2.49 (2) | 1.99 (15) | 0.76 (13) | 7.49 (15) | 4.51 (15) | 3.73 (14) | 0.84 (14) | 0.77 (14) | 0.77 (13) | 81.7 (14) | 10.891 |
| SQuad | 2.91 (16) | 2.89 (13) | 2.06 (17) | 2.35 (12) | 0.8 (9) | 10.93 (11) | 3.57 (11) | 3.03 (9) | 0.86 (10) | 0.79 (9) | 0.79 (11) | 83.71 (12) | 11.683 |
| dy | 2.93 (15) | 2.97 (11) | 2.14 (13) | 2.56 (8) | 0.78 (12) | 9.58 (12) | 4.4 (13) | 3.28 (13) | 0.85 (13) | 0.78 (13) | 0.77 (13) | 83.2 (13) | 12.65 |
| wataru9871 | 3.18 (2) | 4.01 (1) | 2.78 (1) | 1.36 (19) | 0.56 (19) | -13.88 (19) | 11.25 (19) | 7.98 (19) | 0.82 (17) | 0.73 (17) | 0.51 (19) | 79.7 (18) | 13.958 |
| IASP_Q | 2.94 (13) | 2.77 (16) | 2.14 (13) | 2.25 (13) | 0.76 (13) | 6.0 (17) | 5.21 (16) | 4.31 (15) | 0.83 (15) | 0.74 (15) | 0.69 (16) | 80.03 (17) | 15.075 |
| hanhw96 | 2.63 (18) | 2.42 (18) | 1.87 (18) | 1.91 (17) | 0.72 (15) | 8.28 (13) | 4.41 (14) | 4.89 (16) | 0.83 (15) | 0.74 (15) | 0.7 (15) | 81.66 (15) | 15.75 |
| SEES | 2.88 (17) | 2.8 (15) | 2.15 (11) | 1.99 (15) | 0.68 (17) | 8.07 (14) | 5.78 (17) | 6.59 (18) | 0.79 (18) | 0.66 (18) | 0.54 (18) | 71.74 (19) | 16.758 |
| noisy | 1.84 (19) | 1.69 (19) | 1.56 (19) | 1.37 (18) | 0.61 (18) | 2.53 (18) | 7.92 (18) | 5.51 (17) | 0.75 (19) | 0.62 (19) | 0.63 (17) | 81.29 (16) | 18.075 |