Datasets:
File size: 6,618 Bytes
92737de b7a6a33 92737de 53b9601 a21a537 53b9601 a21a537 53b9601 a21a537 53b9601 92737de 53b9601 92737de b7a6a33 92737de | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 | ---
license: cc-by-4.0
pretty_name: Lombard GRID Cross-Modal Utterance Retrieval
task_categories:
- any-to-any
tags:
- mteb
- moeb
- audio-video-retrieval
- cross-view-retrieval
- speech-retrieval
dataset_info:
- config_name: condition_pairs
features:
- name: plain_recording_id
dtype: string
- name: lombard_recording_id
dtype: string
splits:
- name: test
num_bytes: 23760
num_examples: 540
download_size: 13102
dataset_size: 23760
- config_name: matching_utterances
features:
- name: audio_id
dtype: string
- name: front_video_id
dtype: string
- name: profile_video_id
dtype: string
splits:
- name: test
num_bytes: 36720
num_examples: 540
download_size: 19393
dataset_size: 36720
- config_name: media
features:
- name: recording_id
dtype: string
- name: audio_id
dtype: string
- name: front_video_id
dtype: string
- name: profile_video_id
dtype: string
- name: front_video
dtype: video
- name: profile_video
dtype: video
- name: audio
dtype: audio
splits:
- name: test
num_bytes: 538091712
num_examples: 1080
download_size: 498569082
dataset_size: 538091712
configs:
- config_name: condition_pairs
data_files:
- split: test
path: condition_pairs/test-*
- config_name: matching_utterances
data_files:
- split: test
path: matching_utterances/test-*
- config_name: media
data_files:
- split: test
path: media/test-*
---
# Lombard GRID Cross-Modal Utterance Retrieval
Four MTEB/MOEB utterance-retrieval tasks derived from the
[Lombard GRID corpus](https://zenodo.org/records/3736465): audio-to-video, video-to-audio,
frontal-to-profile video, and plain-to-Lombard video+audio. Relevance always
requires the same utterance recording or the same speaker-and-sentence pair;
speaker identity alone is never relevant.
The source paper introduced the corpus but did not define these retrieval tasks.
Relevance is derived from native recording, speaker, sentence-code, condition,
and camera-view labels.
## Frozen evaluation protocol
- Speakers: 54 (`s2` through `s55`; `s1` was excluded by the source)
- Selected sentence codes: 540 (10 per speaker)
- Published media recordings: 1080
- Matching-task recordings: 540 (5 plain and 5 Lombard per speaker)
- Selection seed: `mteb-lombard-grid-retrieval-v2`
For every speaker, eligible sentence codes present in both conditions and all
three media streams are ordered by SHA-256 over the fixed seed, speaker, and
sentence code. The first ten valid pairs are retained. Five plain and five
Lombard recordings per speaker are then selected deterministically for the three
same-recording tasks. Opaque IDs are published; speaker, condition, sentence
code, transcription, and other text are not encodable dataset features.
| Task | Queries | Corpus | Qrels | Positives/query |
|---|---:|---:|---:|---:|
| Audio to frontal/profile video | 540 | 1,080 | 1,080 | 2 |
| Frontal/profile video to audio | 1,080 | 540 | 1,080 | 1 |
| Frontal video to profile video | 540 | 540 | 540 | 1 |
| Plain frontal video+audio to Lombard frontal video+audio | 540 | 540 | 540 | 1 |
## Source audit and release discrepancies
The official JSON archive contains 5,340 rows, while each
media archive contains 5,390 files. All three
media archives have exactly the same recording filenames. The media restore 50
`s31` recordings absent from JSON. `s51` has only 40 plain and 50 Lombard files,
rather than the advertised 50 of each. `s14` has 51 plain and 49 Lombard rows,
including a duplicate `prwr3a` recording key. The JSON metadata labels 69
recordings as `WRONG`. Media filenames mark 70: the additional one is among the
50 media-only `s31` recordings. All 70, plus the one legacy-named duplicate, are
excluded from selection. Four frontal MOV files lack a `moov` atom and are corrupt:
`s32_l_pwip9p`, `s32_p_bwwj2n`, `s33_l_pwajza`, and `s33_p_sgwq2s`.
The deterministic selection required 0 fallback(s). The selected
protocol remains exactly balanced after exclusions.
## Media processing and validation
The released MOV files are already H.264/yuv420p visual-only clips, so
2,160 selected videos are copied without
transcoding. 0 video(s) required a lossless video-stream remux to
remove embedded audio. Separate source WAV files are copied without transcoding.
All 1080 frontal videos,
1080 profile videos, and
1080 audio files were decoded
completely with TorchCodec during construction. Matching source filename stems
establish audiovisual correspondence. Selected video/audio duration differences
were checked and paired decoding succeeded. The source paper reports
correlation-based audiovisual alignment before utterance extraction; this
construction did **not** independently verify signal-level synchronization.
The shared configs avoid storing the same media repeatedly across four tasks:
- `media/test`: opaque recording and modality IDs, frontal video, profile video, audio
- `matching_utterances/test`: opaque audio, frontal-video, and profile-video IDs
- `condition_pairs/test`: opaque plain- and Lombard-recording IDs
The MTEB task loaders project these configs into the standard query, corpus, and
qrel structures without exposing source labels to embedding models.
## Evaluation
The primary metric for all four tasks is nDCG@10. Other standard MTEB retrieval
metrics are reported as secondary results. These protocols are newly derived, so
there is no source-paper retrieval score to reproduce.
## License and attribution
The source corpus is released under the
[Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/).
Please attribute the original authors and cite the paper below. The MTEB task
metadata and this card both use `cc-by-4.0`.
## Responsible use
The source contains identifiable faces and voices. Although these tasks evaluate
utterance correspondence rather than biometric identification, the representations
may still encode identity and demographic attributes. Users should consider
participant consent, privacy, applicable biometric-data law, subgroup behavior,
and downstream misuse before training or deploying related systems.
## Citation
```bibtex
@article{alghamdi2018corpus,
author = {Alghamdi, Najwa and Maddock, Steve and Marxer, Ricard and Barker, Jon and Brown, Guy J.},
title = {A corpus of audio-visual Lombard speech with frontal and profile views},
journal = {The Journal of the Acoustical Society of America},
volume = {143},
number = {6},
pages = {EL523--EL529},
year = {2018},
doi = {10.1121/1.5042758},
}
```
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