Spoken Language Understanding

Benchmarks archive 2025-07-28

5 leaderboard tables shown for this task, 5 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

14 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

2 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 135 papers with code (550 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces
  25 May 2018 16 repositories listed Syntology ran 1 of 15 samples · 14 unverified
  This paper presents the machine learning architecture of the Snips Voice Platform, a software solution to perform Spoken Language Understanding on microprocessors typical of IoT devices.
• SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering
  10 Dec 2018 6 repositories listed
  Conversational question answering (CQA) is a novel QA task that requires understanding of dialogue context.
• SpeechBrain: A General-Purpose Speech Toolkit
  8 Jun 2021 4 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  SpeechBrain is an open-source and all-in-one speech toolkit.
• Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding
  6 Jul 2022 3 repositories listed
  Conformer has proven to be effective in many speech processing tasks.
• Using Speech Synthesis to Train End-to-End Spoken Language Understanding Models
  21 Oct 2019 3 repositories listed Syntology ran 1 of 12 samples · 11 unverified
  End-to-end models are an attractive new approach to spoken language understanding (SLU) in which the meaning of an utterance is inferred directly from the raw audio without employing the standard pipeline composed of a…
• Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening Comprehension
  1 Apr 2018 3 repositories listed
  Reading comprehension has been widely studied.
• MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark
  5 Jun 2025 2 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)
  To address this gap, we introduce MMSU, a comprehensive benchmark designed specifically for understanding and reasoning in spoken language.
• RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate Sector
  13 Dec 2024 2 repositories listed
  To tackle these challenges, we propose the SLUTQA framework, which integrates large language models with spoken language understanding tasks to enhance retrieval and answering accuracy.
• Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition Errors
  25 Oct 2023 2 repositories listed
  This paper proposes a method for investigating the impact of speech recognition errors on the performance of natural language understanding models.
• LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
  7 Oct 2023 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  Previous mainstream audio-and-text LLMs use discrete audio tokens to represent both input and output audio; however, they suffer from performance degradation on tasks such as automatic speech recognition, speech-to-text…
• A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Tasks
  18 May 2023 2 repositories listed
  Conformer, a convolution-augmented Transformer variant, has become the de facto encoder architecture for speech processing due to its superior performance in various tasks, including automatic speech recognition (ASR),…
• Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models
  29 Jun 2022 2 repositories listed
  In Spoken Language Understanding (SLU) the task is to extract important information from audio commands, like the intent of what a user wants the system to do and special entities like locations or numbers.
• ESPnet-SLU: Advancing Spoken Language Understanding through ESPnet
  29 Nov 2021 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  However, there are few open source toolkits that can be used to generate reproducible results on different Spoken Language Understanding (SLU) benchmarks.
• From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding
  15 May 2021 2 repositories listed
  To tackle the challenge, we propose a joint learning approach, with English SLU training data and non-English auxiliary tasks from raw text, syntax and translation for transfer.
• Timers and Such: A Practical Benchmark for Spoken Language Understanding with Numbers
  4 Apr 2021 2 repositories listed
  This paper introduces Timers and Such, a new open source dataset of spoken English commands for common voice control use cases involving numbers.
• SPLAT: Speech-Language Joint Pre-Training for Spoken Language Understanding
  5 Oct 2020 2 repositories listed
  Besides conducting a self-supervised masked language modeling task on the two individual modules using unpaired speech and text, SPLAT aligns representations from the two modules in a shared latent space using a small…
• Learning Spoken Language Representations with Neural Lattice Language Modeling
  6 Jul 2020 2 repositories listed
  Pre-trained language models have achieved huge improvement on many NLP tasks.
• EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators
  2 Dec 2019 2 repositories listed
  These neural models annotate the emotion corpora with dialogue act labels, and an ensemble annotator extracts the final dialogue act label.
• CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding
  16 Sep 2019 2 repositories listed
  Spoken Language Understanding (SLU) mainly involves two tasks, intent detection and slot filling, which are generally modeled jointly in existing works.
• A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding
  5 Sep 2019 2 repositories listed
  In our framework, we adopt a joint model with Stack-Propagation which can directly use the intent information as input for slot filling, thus to capture the intent semantic knowledge.
• A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling
  30 Jun 2019 2 repositories listed
  The joint model for the two tasks is becoming a tendency in SLU.
• Mitigating the Impact of Speech Recognition Errors on Spoken Question Answering by Adversarial Domain Adaptation
  16 Apr 2019 2 repositories listed
  Spoken question answering (SQA) is challenging due to complex reasoning on top of the spoken documents.
• Speech Model Pre-training for End-to-End Spoken Language Understanding
  7 Apr 2019 2 repositories listed
  Whereas conventional spoken language understanding (SLU) systems map speech to text, and then text to intent, end-to-end SLU systems map speech directly to intent through a single trainable model.
• Spoken Language Understanding on the Edge
  30 Oct 2018 2 repositories listed Syntology ran 1 of 14 samples · 13 unverified
  We consider the problem of performing Spoken Language Understanding (SLU) on small devices typical of IoT applications.
• Slot-Gated Modeling for Joint Slot Filling and Intent Prediction
  1 Jun 2018 2 repositories listed
  Attention-based recurrent neural network models for joint intent detection and slot filling have achieved the state-of-the-art performance, while they have independent attention weights.
• "KAN you hear me?" Exploring Kolmogorov-Arnold Networks for Spoken Language Understanding
  26 May 2025 1 repository listed
  Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional neural architectures, yet their application to speech processing remains under explored.
• "Alexa, can you forget me?" Machine Unlearning Benchmark in Spoken Language Understanding
  21 May 2025 1 repository listed
  Machine unlearning, the process of efficiently removing specific information from machine learning models, is a growing area of interest for responsible AI.
• QUADS: QUAntized Distillation Framework for Efficient Speech Language Understanding
  19 May 2025 1 repository listed
  Spoken Language Understanding (SLU) systems must balance performance and efficiency, particularly in resource-constrained environments.
• LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams
  24 Apr 2025 1 repository listed
  Long-context understanding poses significant challenges in natural language processing, particularly for real-world dialogues characterized by speech-based elements, high redundancy, and uneven information density.
• Measuring the Effect of Transcription Noise on Downstream Language Understanding Tasks
  19 Feb 2025 1 repository listed
  For instance, we find that task models can tolerate a certain level of noise, and are affected differently by the types of errors in the transcript.

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.