---
license: cc-by-4.0
mutilinguality:
- monolingual
task_categories:
- audio-text-to-text
size_categories:
- 1K<n<10K
source_datasets:
- original
pretty_name: BLAB (Brutally Long Audio Bench)
tags:
- speech
- audio
- speech-llm
- audio-lm
- long-audio
- spoken-language-understanding
viewer: true
configs:
- config_name: word_localization
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: question
        dtype: string
      - name: answer_type
        dtype: string
      - name: groundtruth
        dtype: LargeList
        inner_dtype:
          - name: word
            dtype: string
          - name: start
            dtype: float32
          - name: end
            dtype: float32
- config_name: advertisement_localization
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: question
        dtype: string
      - name: answer_type
        dtype: string
      - name: groundtruth
        dtype: Struct
        fields:
          - name: ads_segment
            dtype: LargeList
            inner_dtype:
              - name: text
                dtype: string
              - name: start
                dtype: float32
              - name: end
                dtype: float32
          - name: word_timestamp
            dtype: LargeList
            inner_dtype:
              - name: word
                dtype: string
              - name: start
                dtype: float32
              - name: end
                dtype: float32

- config_name: named_entity_localization
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: question
        dtype: string
      - name: answer_type
        dtype: string
      - name: groundtruth
        dtype: Struct
        fields:
          - name: entities
            dtype: LargeList
            inner_dtype:
              - name: entity_type
                dtype: string
              - name: entity
                dtype: string
              - name: start
                dtype: float32
              - name: end
                dtype: float32
          - name: word_timestamp
            dtype: LargeList
            inner_dtype:
              - name: word
                dtype: string
              - name: start
                dtype: float32
              - name: end
                dtype: float32
- config_name: speaker_number_estimation
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: question
        dtype: string
      - name: groundtruth
        dtype: Sequence # It's a list, even if it might contain one element
        inner_dtype:
          dtype: int32 # The type of elements within the list
- config_name: entire_duration
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: question
        dtype: string
      - name: groundtruth
        dtype: float32
- config_name: event_duration
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: question
        dtype: string
      - name: answer_type
        dtype: string
      - name: groundtruth
        dtype: float32
- config_name: emotion_ranking
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: type
        dtype: string
      - name: question
        dtype: string
      - name: correct_option
        dtype: string
      - name: option_A
        dtype: string
      - name: option_B
        dtype: string
      - name: option_C
        dtype: string
      - name: option_D
        dtype: string
      - name: option_E
        dtype: string
      - name: correct_answer
        dtype: string
- config_name: emotion_reasoning
  features:
      - name: video_url
        dtype: string
      - name: audio
        dtype: string
      - name: type
        dtype: string
      - name: question
        dtype: string
      - name: correct_option
        dtype: string
      - name: option_A
        dtype: string
      - name: option_B
        dtype: string
      - name: option_C
        dtype: string
      - name: option_D
        dtype: string
      - name: correct_answer
        dtype: string
---


# BLAB: Brutally Long Audio Bench


## Dataset Summary
Brutally Long Audio Bench (BLAB) is a challenging long-form audio benchmark that evaluates audio LMs on localization, duration estimation, emotion, and counting tasks using audio segments averaging 51 minutes in length. BLAB consists of 833+ hours of diverse, full-length Youtube audio clips, each paired with human-annotated, text-based natural language questions and answers. Our audio data were collected from permissively licensed sources and underwent a human-assisted filtering process to ensure task compliance.

NB: This data should only be used for evaluation purposes and not for model training.



## Tasks Covered in BLAB

### Localization
* **Word Localization:** Locate the exact start and end times of specific words within the audio.
* **Named Entity Localization:** Detect and locate the exact start and end times of named entities (e.g., people, organizations, locations).
* **Advertisement Localization:** Locate and transcribe advertisement segments within a podcast.

### Counting
* **Speaker Number Estimation:** Determine the number of unique speakers present in the full audio segment.

### Duration
* **Event Duration:** Calculate the duration of specific acoustic events (e.g., laughter in a comedy special, question-and-answer segments in a panel session, or a particular speaker’s total speaking time in a meeting) within an audio sample,.
* **Entire Duration:** Estimate the total duration of an audio file, expressed in seconds.

### Emotion
* **Emotion Reasoning:** Reason over emotional expressions conveyed in the audio.
* **Emotion Ranking:** Rank different emotional expressions of speech and non-verbal sound present in the audio.



## Dataset Structure

To load a specific task from BLAB, you'll need to specify its configuration name. Keep in mind that **BLAB provides URLs to the YouTube audio files, not the actual audio files themselves.** You'll need to download the audio from these URLs separately.

```python
from datasets import load_dataset

# Load the Word Localization task
word_localization_data = load_dataset("oreva/blab_long_audio", "word_localization")


# Load the Named Entity Localization task
named_entity_localization_data = load_dataset("oreva/blab_long_audio", "named_entity_localization")

# You can load any other task similarly:
# speaker_number_estimation_data = load_dataset("oreva/blab_long_audio", "speaker_number_estimation")
# entire_duration_data = load_dataset("oreva/blab_long_audio", "entire_duration")
# event_duration_data = load_dataset("oreva/blab_long_audio", "event_duration")
# emotion_reasoning_data = load_dataset("oreva/blab_long_audio", "emotion_reasoning")
# emotion_ranking_data = load_dataset("oreva/blab_long_audio", "emotion_ranking")

```

# Citation

```
@misc{ahia2025blabbrutallylongaudio,
      title={BLAB: Brutally Long Audio Bench},
      author={Orevaoghene Ahia and Martijn Bartelds and Kabir Ahuja and Hila Gonen and Valentin Hofmann and Siddhant Arora and Shuyue Stella Li and Vishal Puttagunta and Mofetoluwa Adeyemi and Charishma Buchireddy and Ben Walls and Noah Bennett and Shinji Watanabe and Noah A. Smith and Yulia Tsvetkov and Sachin Kumar},
      year={2025},
      eprint={2505.03054},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2505.03054},
}

```