# Voices Obscured in Complex Environmental Settings (VOICES) corpus

arXiv: https://arxiv.org/abs/1804.05053 · HTML: https://mlsanity.com/paper/1804.05053/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Apr 2018.

## Built on by (most cited first, 28 of 28)

- [Learning Audio-Visual Dereverberation](https://mlsanity.com/paper/2106.07732/) (2021)
- [MESH2IR: Neural Acoustic Impulse Response Generator for Complex 3D Scenes](https://mlsanity.com/paper/2205.09248/) (2022)
- [The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios](https://mlsanity.com/paper/2306.13734/) (2023)
- [NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcription](https://mlsanity.com/paper/2401.08887/) (2024)
- [AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs](https://mlsanity.com/paper/2306.05562/) (2023)
- [A Speaker Verification Backend with Robust Performance across Conditions](https://mlsanity.com/paper/2102.01760/) (2021)
- [Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech](https://mlsanity.com/paper/2402.16321/) (2024)
- [Compass: SLO-aware Query Planner for Compound AI Serving at Scale](https://mlsanity.com/paper/2504.16397/) (2025)
- [BERSting at the Screams: A Benchmark for Distanced, Emotional and Shouted Speech Recognition](https://mlsanity.com/paper/2505.00059/) (2025)
- [Mega-ASR: Towards In-the-wild^2 Speech Recognition via Scaling up Real-world Acoustic Simulation](https://mlsanity.com/paper/2605.19833/) (2026)
- [Large-scale learning of generalised representations for speaker recognition](https://mlsanity.com/paper/2210.10985/) (2022)
- [How Would It Sound? Material-Controlled Multimodal Acoustic Profile Generation for Indoor Scenes](https://mlsanity.com/paper/2508.02905/) (2025)
- [MultiSV: Dataset for Far-Field Multi-Channel Speaker Verification](https://mlsanity.com/paper/2111.06458/) (2021)
- [Speech enhancement with frequency domain auto-regressive modeling](https://mlsanity.com/paper/2309.13537/) (2023)
- [Synthetic Wave-Geometric Impulse Responses for Improved Speech Dereverberation](https://mlsanity.com/paper/2212.05360/) (2022)
- [Diff-SV: A Unified Hierarchical Framework for Noise-Robust Speaker Verification Using Score-Based Diffusion Probabilistic Models](https://mlsanity.com/paper/2309.08320/) (2023)
- [Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption](https://mlsanity.com/paper/2503.17577/) (2025)
- [Inclusivity of AI Speech in Healthcare: A Decade Look Back](https://mlsanity.com/paper/2505.10596/) (2025)
- [Recent Trends in Distant Conversational Speech Recognition: A Review of CHiME-7 and 8 DASR Challenges](https://mlsanity.com/paper/2507.18161/) (2025)
- [WhiSQA: Non-Intrusive Speech Quality Prediction Using Whisper Encoder Features](https://mlsanity.com/paper/2508.02210/) (2025)
- [RW-Voice-EQ Bench: A Real World Benchmark for Evaluating Voice AI Systems](https://mlsanity.com/paper/2607.14846/) (2026)
- [Parameterized Channel Normalization for Far-field Deep Speaker Verification](https://mlsanity.com/paper/2109.12056/) (2021)
- [RescueSpeech: A German Corpus for Speech Recognition in Search and Rescue Domain](https://mlsanity.com/paper/2306.04054/) (2023)
- [MR-RawNet: Speaker verification system with multiple temporal resolutions for variable duration utterances using raw waveforms](https://mlsanity.com/paper/2406.07103/) (2024)
- [How Does a Deep Neural Network Look at Lexical Stress in English Words?](https://mlsanity.com/paper/2508.07229/) (2025)
- [LibriVAD: A Scalable Open Dataset with Deep Learning Benchmarks for Voice Activity Detection](https://mlsanity.com/paper/2512.17281/) (2025)
- [Transcript-Supervised Post-Training of Generative Speech Enhancement on Real Recordings via Reinforce Adjoint Matching](https://mlsanity.com/paper/2609.29405/) (2026)
- [FFASR: Benchmarking Far-Field Automatic Speech Recognition using High-Fidelity Simulated RIRs](https://mlsanity.com/paper/2609.38897/) (2026)

## Abstract (arXiv)

This paper introduces the Voices Obscured In Complex Environmental Settings (VOICES) corpus, a freely available dataset under Creative Commons BY 4.0. This dataset will promote speech and signal processing research of speech recorded by far-field microphones in noisy room conditions. Publicly available speech corpora are mostly composed of isolated speech at close-range microphony. A typical approach to better represent realistic scenarios, is to convolve clean speech with noise and simulated room response for model training. Despite these efforts, model performance degrades when tested against uncurated speech in natural conditions. For this corpus, audio was recorded in furnished rooms with background noise played in conjunction with foreground speech selected from the LibriSpeech corpus. Multiple sessions were recorded in each room to accommodate for all foreground speech-background noise combinations. Audio was recorded using twelve microphones placed throughout the room, resulting in 120 hours of audio per microphone. This work is a multi-organizational effort led by SRI International and Lab41 with the intent to push forward state-of-the-art distant microphone approaches in signal processing and speech recognition.