Switchboard

The Switchboard dataset is an unlabeled target domain used to evaluate the performance of speech recognition systems, particularly in the context of unsupervised domain adaptation.

Papers using Switchboard (25)

Confidence Score Based Conformer Speaker Adaptation For Speech Recognition2022 · 13 citesTwo-pass Decoding And Cross-adaptation Based System Combination Of End-to-end Conformer And Hybrid TDNN ASR Systems2022 · 6 citesImproving Speech Recognition Error Prediction For Modern And Off-the-shelf Speech Recognizers2024 · 4 citesUnsupervised Model-based Speaker Adaptation Of End-to-end Lattice-free MMI Model For Speech Recognition2022 · 1 citesTeaching the Teachers: Boosting unsupervised domain adaptation in speech recognition by ensemble update2026Chain-of-Thought Training for Open E2E Spoken Dialogue Systems2025Towards One-bit ASR: Extremely Low-bit Conformer Quantization Using Co-training and Stochastic Precision2025Adaptable End-to-end ASR Models Using Replaceable Internal Lms And Residual Softmax2023 · 8 citesDecoder-only Architecture For Speech Recognition With CTC Prompts And Text Data Augmentation2023 · 1 citesSpeaker Adaptation For End-to-end Speech Recognition Systems In Noisy Environments2022Svarah: Evaluating English ASR Systems on Indian Accents2023 · 3 citesHMM vs. CTC for Automatic Speech Recognition: Comparison Based on Full-Sum Training from Scratch2022 · 1 citesAdaptable End-to-End ASR Models using Replaceable Internal LMs and Residual Softmax2023 · 1 citesDecoder-only Architecture for Speech Recognition with CTC Prompts and Text Data Augmentation2023 · 1 citesToward Zero Oracle Word Error Rate on the Switchboard Benchmark2022Two-pass Decoding and Cross-adaptation Based System Combination of End-to-end Conformer and Hybrid TDNN ASR Systems2022Confidence Score Based Conformer Speaker Adaptation for Speech Recognition2022CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representations2022Streaming Joint Speech Recognition and Disfluency Detection2022Speaker Adaptation for End-To-End Speech Recognition Systems in Noisy Environments2022Unsupervised Model-based speaker adaptation of end-to-end lattice-free MMI model for speech recognition2022Analyzing And Improving Neural Speaker Embeddings for ASR2023Connecting Speech Encoder and Large Language Model for ASR2023Progressive unsupervised domain adaptation for ASR using ensemble models and multi-stage training2024Automatic Speech Recognition System-Independent Word Error Rate Estimation2024