Training models for speech recognition, sound event detection, or language identification
Struggling with delays in labeling complex or noisy audio data
Supplying labeled audio for security, healthcare, and media industries
Needing fast and accurate audio labeling to meet client demands
Using ML for voice assistants, customer analytics, or sound monitoring
Overwhelmed by mass volumes of raw data needing consistent labeling
Creating labeled audio datasets for studies or language research
Lacking time and resources for manual audio labeling
Improve your model’s ability to recognize spoken words with accurately labeled audio data.
Train models to detect emotions in audio using sentiment-labeled voice data.
Identify and distinguish between multiple speakers in an audio file through precise speaker annotation.
Classify environmental sounds or events in audio recordings with annotated sound categories.
Convert speech to text with accurately transcribed and annotated audio datasets.
Improve your model’s ability to recognize spoken words with accurately labeled audio data.
Train models to detect emotions in audio using sentiment-labeled voice data.
Identify and distinguish between multiple speakers in an audio file through precise speaker annotation.
Classify environmental sounds or events in audio recordings with annotated sound categories.
Convert speech to text with accurately transcribed and annotated audio datasets.
Submit your audio data for a free trial and assess our labeling services risk-free.
Review the results to ensure they meet your accuracy and budget requirements.
Get a proposal tailored to your specific audio labeling project needs.
Begin the audio labeling process with our team to move your project forward.
Receive your labeled audio data on time, keeping your project on track.
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Label Your Data were genuinely interested in the success of my project, asked good questions, and were flexible in working in my proprietary software environment.
Kyle Hamilton
PhD Researcher at TU Dublin
Trusted by ML Professionals
Audio labeling involves tagging parts of an audio file, like speech, sounds, or specific speakers, to make it easier for machine learning models to process. Whether identifying key words in a conversation or distinguishing different sound events, audio labeling improves AI systems like virtual assistants or audio monitoring tools.
Annotating audio files involves breaking down the audio and tagging key elements like speech segments, sounds, or speaker changes. You’d typically use software to mark these sections, which can get complicated with overlapping sounds or background noise. To avoid these hurdles, you can trust the process to Label Your Data. We handle the entire audio labeling process so you can focus on building your models.
At Label Your Data, we use our in-house tools specifically designed for accurate and efficient audio annotation. However, if you have a preferred tool, our team is flexible and can work with the platform of your choice. We ensure your project is managed seamlessly, no matter the tool used.