Overview
FlashVoice performs speech-to-text entirely on your device, without uploading audio or video files to the cloud.
Local speech recognition models are fast and privacy-friendly, but transcription quality can vary depending on language settings, audio conditions, and post-processing choices.
This guide explains where transcription accuracy comes from in FlashVoice, and how you can improve results through correct setup and workflow.
Understanding the Transcription Pipeline
To improve accuracy, it helps to understand how transcription works in FlashVoice:
- Speech Recognition
Audio is converted into raw text using a local speech recognition model. - Post-processing (Optional)
The raw transcription can then be refined using AI correction and custom vocabulary.
Different optimization strategies apply to each stage.
Choose the Correct Transcription Language
Language selection has the largest impact during the speech recognition stage.
FlashVoice supports automatic language detection, but manually selecting the correct language usually produces better results.
Best practices:
- Select the original spoken language whenever possible
- Avoid auto-detect for long or single-language recordings
- Do not mix multiple languages in one file if accuracy is critical
Correct language selection significantly reduces recognition errors at the source.
Use Clear and High-Quality Audio
Audio quality directly affects the speech recognition stage.
To improve accuracy:
- Use recordings with minimal background noise
- Avoid overlapping speech
- Keep a consistent distance between speaker and microphone
- Prefer a single, clear audio source
Cleaner audio allows the recognition model to focus on speech instead of noise.
When to Re-run Transcription
Because transcription is processed locally, you can re-run it without re-uploading files.
Re-running transcription is recommended when:
- The wrong language was selected initially
- Audio quality was improved or replaced
- You want to regenerate raw results before post-processing
Reprocessing is often more effective than manually fixing early recognition errors.
Use AI Correction for Post-processing
After transcription, FlashVoice provides optional AI correction as a post-processing step.
AI correction works on the generated text and can:
- Fix recognition mistakes
- Improve punctuation
- Smooth sentence structure
- Enhance overall readability
This step does not affect the original recognition process, but refines the output text.
Use Custom Vocabulary (Hotwords) in Post-processing
FlashVoice supports Custom Vocabulary (Hotwords) during the post-processing stage.
Custom vocabulary is applied after transcription, not during audio recognition.
It is especially useful for:
- Personal names
- Product or company names
- Technical terminology
- Acronyms and abbreviations
By providing a list of important words, you help the AI correction step adjust and normalize the transcription output more accurately.
When Local Transcription Works Best
Local transcription in FlashVoice performs best when:
- The correct language is selected before transcription
- Audio is clear and consistent
- Transcription is re-run when setup changes
- AI correction and custom vocabulary are applied thoughtfully
Understanding which optimizations apply to which stage helps avoid unrealistic expectations.
Summary
Improving local transcription accuracy in FlashVoice is a combination of correct recognition setup and effective post-processing.
By selecting the right language, using clean audio, re-running transcription when needed, and refining results with AI correction and custom vocabulary, you can achieve reliable, high-quality transcripts — fully offline and privacy-first.