Audio to Text Converter-English audio to text + IPA
AI-powered English transcription with precise IPA.
Converts video audio to text with phonetic transcription.
Upload a video to extract text
How to convert video audio to text?
Edit the text converted from my video
Summarize the audio content of my uploaded video
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Audio to Text Converter — purpose and core design
Audio to Text Converter is a specialized transcription partner that focuses solely on the audio track of your uploaded videos or audio files. It delivers a two-part output: (1) an accurate English orthographic transcription (what was said), and (2) a phonetic transcription using IPA symbols that captures how it was actually pronounced, including subtle, non-meaning-changing details (allophonic variation, reduction, coarticulation, etc.). The design goal is to bridge everyday readability with research-grade phonetic detail. Example (short clip): Text line: "We should've gone earlier, but traffic was awful." Phonetic line: [wi ʃʊɾəv ɡɑn ˈɝliɚ | bəɾ ˈtɹæfɪk wəz ˈɔfəl] (shows flapping /t/→[ɾ], reduction /have/→[əv], rhotic vowels) Scenario 1 (classroom phonetics): A student uploads a 20-second answer from an interview. They receive a readable line for quoting and an IPA line that highlights flapping, vowel reduction, and final devoicing for analysis. Scenario 2 (content creation): A podcaster uploads an episode segment. They get publication-ready text plus IPA that a voice coach uses to fine-tune pacing and target soundsAudio to text converter.
Key functions and how they are applied
High-accuracy English transcription (orthographic)
Example
Input: Casual meeting audio. Output (two lines): "I can finish by Friday, but I'd prefer Monday." [aɪ kən ˈfɪnɪʃ baɪ ˈfɹaɪdeɪ | bəɾ aɪd pɹəˈfɝ ˈmʌndeɪ]
Scenario
Project managers upload call recordings to extract decisions and commitments in clean English. The phonetic line explains why a word sounded different to some listeners (e.g., /t/ in "but I'd" realized as a tap [ɾ]).
Narrow phonetic transcription (IPA) with controllable detail
Example
Utterance: "That butter melted quickly." Text: "That butter melted quickly." Phonetic (narrow): [ðæʔ ˈbʌɾɚ ˈmɛl̪tɪd ˈkʷwɪkli] (glottalization [ʔ] on /t/ in "that", alveolar tap [ɾ] in "butter", dentalization [l̪] before [t], labialization [kʷ] before [w])
Scenario
Linguistics labs, pronunciation coaches, and accent analysts request narrow detail to study allophones, coarticulation, and timing, while classrooms may request a slightly broader IPA for teaching.
Accent and dialect highlighting
Example
Word: "water" GenAm: [ˈwɔɾɚ] Non-rhotic (e.g., some Southern British): [ˈwɔːtə] NYC realization (example): [ˈwɔɾə] (variable rhoticity, schwa final)
Scenario
Dialect coaches compare realizations across speakers to plan targeted drills; researchers document regional features (rhoticity, vowel quality, t-flapping vs. t-retention).
Timestamped segmentation (optional) for captions/subtitles
Example
00:00–00:04 "Let’s circle back after lunch." [lɛʔs ˈsɝkəl bæk ˈæfɾɚ lʌnʧ] 00:04–00:08 "I'll email the draft." [aɪl ˈimeɪl ðə dɹæft]
Scenario
Video teams need ready-to-drop captions. We segment by time and keep the two-line format per segment, enabling quick subtitle creation without retyping.
Disfluency and uncertainty handling
Example
Text: "We— uh— we can move it to ten." Phonetic: [wi | ə | wi kən ˈmuːv ɪɾ tə tɛn] (Disfluencies preserved; segments marked. If audio is unclear, we flag like ⟨inaudible⟩ or (?) and provide the best phonetic guess.)
Scenario
User-research teams analyze hesitation, repair, and overlap in interviews. Keeping disfluencies improves conversational analysis and training datasets.
Batch processing across file types (video or audio)
Example
User uploads MP4, MOV, MKV, MP3, WAV. Each file returns the same two-line structure per utterance or per file (user preference).
Scenario
Podcasters or educators dump a whole lecture series; they receive consistent outputs for immediate archiving, search, and study.
Who benefits most
Linguists, phoneticians, and speech scientists
Need narrow, consistent IPA with micro-detail (flapping, aspiration, vowel reduction, devoicing, syllabic consonants). The two-line output supports both citation and analysis without extra tooling.
ESL/EFL learners, teachers, and pronunciation coaches
Orthographic line aids comprehension; the IPA line reveals how target words are actually realized in connected speech (e.g., "want to" → [ˈwɑnə]). Coaches design drills from the phonetic evidence.
Podcasters, YouTubers, and video editors
Get clean text for descriptions and captions plus phonetic lines for voice direction and ADR. Optional timestamps make subtitle workflows straightforward.
Accessibility and localization teams
Create accurate captions/transcripts for compliance and inclusive design while using the IPA layer to guide dubbing, TTS alignment, and consistent name pronunciations.
User-researchers, CX/UX teams, and call-center analysts
Retain disfluencies and repair phenomena for conversation analysis. IPA helps explain perceptual confusions that affect intent detection and training of downstream models.
Educators and students (communication, theater, linguistics)
Leverage readable text for coursework and IPA for performance coaching, speech contests, and lab reports—without juggling separate tools.
How to Use Audio to Text Converter
Visit aichatonline.org for a free trial without login, also no need for ChatGPT Plus.
Open the site to start immediately. This tool works directly in your browser and focuses solely on extracting and transcribing English audio from your uploaded media.
Upload your media
Attach a video or audio file (e.g., MP4, MOV, MKV, MP3, WAV, M4A). Prefer clear English speech, minimal background noise, and a steady mic level. The tool ignores visuals—only the soundtrack is analyzed.
Choose detail level
Tell me if you want a broad or narrow IPA line, any preferred accent reference (e.g., General American, RP), and whether you need timestamps or speaker notes. Mention domain terms (names, jargon) for higher accuracy.
Transcribe and review
I return two lines per segment: (1) the English transcript and (2) a phonetic line capturing the actual pronunciation. I mark ambiguous audio with [unclear] and can flag non-English speech for your confirmation.
Refine and export
Request edits (e.g., punctuation cleanup, removing fillersAudio to Text Guide), formatting (paragraphs, bullets, SRT/VTT-style cues), or terminology corrections. Copy the final text anywhere you need.
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- Interview Analysis
- Lecture Notes
- Meeting Minutes
- Podcast Transcripts
- Accessibility Captions
Common Questions & Detailed Answers
What exactly do you output?
For each passage, I provide two lines: the orthographic English transcript and a phonetic transcription using IPA. The phonetic line reflects how the speaker actually sounds (reductions, linking, flaps, vowel quality), not just dictionary forms.
How do you handle accents, speed, or noisy audio?
I’m optimized for English across accents. For best results, upload the cleanest audio available. If speech is fast or masked by noise, I use context to infer words and mark any uncertain spots with [unclear] or time-stamps you request for quick review.
Can you extract audio from videos, and which formats work?
Yes—upload common video containers like MP4, MOV, or MKV (and audio files like MP3/WAV/M4A). I extract the soundtrack and transcribe only the audio, ignoring on-screen text or visuals.
Do you support broad vs. narrow phonetic transcription?
Absolutely. Ask for a broad IPA (clean, readable) or a narrow IPA (with diacritics for detailed nuances like aspiration, devoicing, vowel length). You can also request specific accent conventions or simplified symbols for readability.
What about privacy and corrections?
Your files are used solely to produce the transcript within this session. Share only what you’re comfortable with. If you spot an error, point to a time or phrase; I’ll revise the text and the IPA line to match the intended wording and pronunciation.