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SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition

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arxiv 1910.13934 v1 pith:YMUWEMCW submitted 2019-10-30 cs.SD cs.CLeess.AS

Lukas Drude , Jens Heitkaemper , Christoph Boeddeker , Reinhold Haeb-Umbach This is my paper · ORCID
classification cs.SDcs.CLeess.AS
keywords databaseseparationsourcebaselineevaluationmeasuresmulti-channelperformance
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We present a multi-channel database of overlapping speech for training, evaluation, and detailed analysis of source separation and extraction algorithms: SMS-WSJ -- Spatialized Multi-Speaker Wall Street Journal. It consists of artificially mixed speech taken from the WSJ database, but unlike earlier databases we consider all WSJ0+1 utterances and take care of strictly separating the speaker sets present in the training, validation and test sets. When spatializing the data we ensure a high degree of randomness w.r.t. room size, array center and rotation, as well as speaker position. Furthermore, this paper offers a critical assessment of recently proposed measures of source separation performance. Alongside the code to generate the database we provide a source separation baseline and a Kaldi recipe with competitive word error rates to provide common ground for evaluation.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. On the Application of Diffusion Models for Simultaneous Denoising and Dereverberation

    eess.AS 2025-08 conditional novelty 6.0 of 10

    For joint denoising and dereverberation with diffusion models, cascade quality depends strongly on which distortion is removed first, and a single mixed-objective model gives the best overall compromise.

  2. Error Analysis in a Modular Meeting Transcription System

    eess.AS 2025-09 conditional novelty 5.0 of 10

    In a modular meeting transcription pipeline, missing speech segments, not primary-to-cross-channel leakage, cause most of the gap to oracle segmentation.

  3. Advances in Speech Separation: Techniques, Challenges, and Future Trends

    cs.SD 2025-08 unverdicted novelty 4.0 of 10

    The declared speech separation survey claims a systematic four-part synthesis with fair benchmark comparisons, but its body is not present in the supplied text, so the claims could not be verified.

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