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The Norwegian Parliamentary Speech Corpus

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arxiv 2201.10881 v1 pith:IW4HMRDF submitted 2022-01-26 cs.CL cs.SDeess.AS

classification cs.CLcs.SDeess.AS
keywords speechdatasetnorwegiansystemnpscannotatedbaselinecontaining
verification ladder T0 review T1 audit T2 compute T3 formal
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The Norwegian Parliamentary Speech Corpus (NPSC) is a speech dataset with recordings of meetings from Stortinget, the Norwegian parliament. It is the first, publicly available dataset containing unscripted, Norwegian speech designed for training of automatic speech recognition (ASR) systems. The recordings are manually transcribed and annotated with language codes and speakers, and there are detailed metadata about the speakers. The transcriptions exist in both normalized and non-normalized form, and non-standardized words are explicitly marked and annotated with standardized equivalents. To test the usefulness of this dataset, we have compared an ASR system trained on the NPSC with a baseline system trained on only manuscript-read speech. These systems were tested on an independent dataset containing spontaneous, dialectal speech. The NPSC-trained system performed significantly better, with a 22.9% relative improvement in word error rate (WER). Moreover, training on the NPSC is shown to have a "democratizing" effect in terms of dialects, as improvements are generally larger for dialects with higher WER from the baseline system.

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  1. Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data

    cs.CL 2025-06 conditional novelty 4.0 of 10

    Whale, a 1.87B-parameter ASR model combining w2v-BERT and E-Branchformer, reports 2.4% WER on Librispeech test-clean and 3.4% CER on CSJ eval3, beating Whisper large-v3 and OWSM v3.1 on those benchmarks.

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