Custom vocabulary
A custom list of words or phrases to improve speech recognition accuracy for specific terms.
Imagine you're trying to get a voice assistant to understand a very specific name, like "Dr. Anya Sharma," or a technical term, like "quantum entanglement." If the system doesn't recognize these words, it might mishear them or ask you to repeat yourself.
A custom vocabulary is like a cheat sheet you give the system. You provide a list of these special words or phrases. The system then pays extra attention to them, making it much more likely to understand you correctly, especially when dealing with jargon, names, or uncommon words.
A custom vocabulary, often implemented as a lexicon or word list, allows users to provide a set of domain-specific terms that a speech recognition (ASR) system should prioritize. This is crucial for improving accuracy when the ASR model might otherwise misinterpret or fail to recognize specialized jargon, proper nouns, or uncommon words. The system typically uses this list to bias its acoustic and language models during decoding, increasing the probability of recognizing the specified terms.
Tradeoffs include potential increases in computational overhead and the risk of over-biasing, which could degrade performance on out-of-vocabulary words if not managed carefully. The effectiveness depends on the quality of the list and how well it's integrated into the ASR pipeline.
Google Gemini's recent focus on its 3.5 Transcribe model highlights the importance of custom vocabularies. This feature allows users to improve the accuracy of speech recognition for specific domains, such as technical jargon or industry-specific terms, which is crucial for transforming audio into actionable data.
- Turn Audio into Action with Gemini 3.5 TranscribeGoogle · Google Cloud Tech on YouTube ·
- How to build with Gemini 3.5 TranscribeGoogle · Google for Developers on YouTube ·
- Google Gemini
- Google Gemini's 3.5 Transcribe product allows users to provide custom vocabularies to improve speech recognition accuracy for specialized terms.
- Pronunciation guide
- A pronunciation guide focuses on how words should sound, wh
- Stop words
- Stop words are common words filtered out in text processing, whereas
- Keyword spotting
- Keyword spotting is about detecting specific trigger words, wh
The concept of custom vocabularies or user-defined lexicons has been a fundamental component of speech recognition systems for decades, evolving with the technology from early rule-based systems to modern deep learning approaches.
If you use a voice assistant like Google Assistant or Siri, try saying a name or a technical term that it usually gets wrong. Then, if the platform allows, look for settings related to 'custom words' or 'voice training' and add that term. See if the assistant understands it better afterward.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- WorkflowImprove medical dictation accuracy with Gemini 3.5 Transcribe custom vocabularyEnhance medical dictation transcription accuracy by configuring custom vocabulary in Gemini 3.5 Transcribe. · 10 min
- Code snippetUsing Gemini 3.5 Transcribe with custom vocabulary and language hintsImprove transcription accuracy by providing custom vocabulary and language hints to Gemini 3.5 Transcribe. · 10 min
- PromptRole-play a student struggling with math for AI tutor simulationSimulate a student's math struggles and uncertainty for AI tutor evaluation. · 5 min
- TemplateReusable workflow templates for healthcare teamsTeams can create and share templates for common workflows like documentation or prior authorizations. · 15 min
- TemplateTemplate for building an AI tool tailored to your workA structured approach to defining and building a custom AI tool for specific business needs. · 15 min
Questions people ask
- Why would a speech system not understand a word by default?
- Speech systems are trained on vast amounts of general language data. Uncommon words, technical jargon, or specific names may not appear frequently enough in this data to be recognized accurately without explicit guidance.
- Can I add any word to a custom vocabulary?
- Generally, yes, but the effectiveness depends on the system's implementation. Some systems might have limits on the number of words or the complexity of phrases you can add.
First seen on Subvolts Aug 26, 2026. Updated Oct 1, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.