Wh

Whisper.cpp and YAKE to Analyse Voice Reflections [iOS]

Hacker News

Whisper.cpp and YAKE to Analyse Voice Reflections [iOS]

Six months ago, I went full-time indie, but I haven't released anything so far. The products just never felt good enough for me to publicly say this is what I'm doing now. To get out of this mindset, I decided to make an app for myself in a week, add monetization, release it and move on. The app idea was simple: Reflect on your day by answering the same four questions out loud. The answers are transcribed and with regular use you can see what influences you the most and take action. All on-device, as otherwise I wouldn't feel comfortable sharing my thoughts. I had all core features working within a day by simply modifying an existing example app. However I was dissatisfied with iOS's built-in offline transcription due to a lack of punctuation and the speech recognition permission prompt that made it seem like data would leave the device. Decided to use whisper.cpp [0] (small model) instead. This change, lead to many others, as I now felt too little of the app's code was mine. e.g.: - Added automatic mood analysis. First using sentiment analysis, then changed to a statistical approach - Show trends: First implemented TextRank to provide a summary for an individual day, then changed it to extract keywords to spot trends over weeks and months. Replaced TextRank with KeyBERT for speed and n-grams, then BERT-SQuAD, and ended on a modified YAKE [1] for subjectively better results. (Do you know of a better approach?) As a result, this tiny app took me over a month, but it still has its flaws: - Transcription is not live but performed on recordings, so if you immediately want the transcript of your most recent answer, you have to wait. - Mood and keyphrase extraction are optimized for my languages and way of speaking, so they might not generalize well. - Music in the background can result in nearly empty transcripts. Nevertheless, after using the app regularly and enjoying it, I feel ready to release. Hope you will find the app useful too. [0] Show HN: Whisper.cpp https://news.ycombinator.com/item?id=33877893 [1] YAKE: https://github.com/LIAAD/yake

Share card

Actual performance

6points
3comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, recordings · Missing: mac, agents, macos
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: ios, month, answers · Missing: mobile apps, personal, entrepreneurs
63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Pl
Planar Reflections in WebGL67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Planar Reflections in WebGL

Hacker News1
Re
Reflections and Takeaways from Deconstruct Conference42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Reflections and Takeaways from Deconstruct Conference

Hacker News2
iO
iOS Grocery List App Powered by Whisper and GPT468%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

iOS Grocery List App Powered by Whisper and GPT4

Hacker News6
Wh
Whisper clone in Indonesia50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Whisper clone in Indonesia

Hacker News1
Wh
Whisper (Berglas for AWS and Azure)39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Whisper (Berglas for AWS and Azure)

Hacker News1
Al
Aligning Whisper Transcripts with Descript54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Aligning Whisper Transcripts with Descript

Hacker News1
Wh
Whistle – Offline, private voice transcription using whisper38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Whistle – Offline, private voice transcription using whisper

Hacker News2
Wh
Whisper v3 API59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Whisper v3 API

Hacker News5
Ch
Chat with Zephyr 7B over voice message using whisper.cpp and llama.cpp59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Chat with Zephyr 7B over voice message using whisper.cpp and llama.cpp

Hacker News3
Em
Emacs and Whisper and ChatGPT Proof of Concept40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Emacs and Whisper and ChatGPT Proof of Concept

Hacker News3