Record audio, transcribe it with Groq, and process it with AI

Recording a thought or conversation is easy; turning the recording into something useful usually takes longer. You may need to locate the relevant passage, convert speech into editable text, correct names, and then reorganize that text into minutes, a summary, or a list of actions. When every step belongs to a different tool, the workflow quickly becomes a sequence of manual transfers.

AssistRecorder brings those steps into a native Android workflow while keeping their boundaries visible. It manages audio, can request a transcription from Groq Speech-to-Text, and lets the user send an editable prompt and transcript to an LLM client of their choice. The external answer can return to local storage as readable Markdown. AssistRecorder does not include its own LLM chat.

From recording to a structured result

A typical AssistRecorder workflow looks like this:

1. Start a recording inside the app, from its widget, or through a device gesture or button after configuring AssistRecorder as the default assistant.
2. Stop the recording and keep the resulting M4A audio locally.
3. Listen to the file and, if necessary, trim it without re-encoding the M4A audio.
4. Explicitly start a Groq transcription. The audio is sent to Groq at this point, not merely because it was recorded.
5. Review and edit the resulting transcript and its title.
6. Select a template and adjust its name or prompt to suit the intended result.
7. Share the prompt and transcript via Android ACTION_SEND to the chosen LLM client.
8. If desired, paste the external result back into AssistRecorder for local storage and Markdown display.

This sequence distinguishes recording on the phone, speech recognition by Groq, and text processing in another app.

Starting a recording in three ways

The most direct option is to use the Start and Stop controls in AssistRecorder. A widget also gives access to recording from the Android home screen.

A third route is available after AssistRecorder has been configured as Android’s default assistant. A device gesture or button can then trigger Start or Stop. The exact gesture or button is determined by the device’s Android controls, and the route only becomes available after the default-assistant setup has been completed.

AssistRecorder creates mono M4A recordings using AAC at 48 kHz. It offers bit rates of 32, 64, and 96 kbit/s. These choices make the recording settings explicit while keeping the output in one supported format throughout the rest of the workflow.

Reviewing, trimming, importing, and exporting audio

AssistRecorder’s player provides 15-second and one-minute jumps, making it possible to revisit a nearby phrase or move across a longer section.

M4A trimming is lossless, so a file can be shortened without another lossy encoding pass.

Existing files can be imported and taken through the same steps. Recordings can also be exported or shared. AssistRecorder does not require general storage access for export.

Groq transcription with Bring Your Own Key

Speech recognition is provided through Groq Speech-to-Text using a BYOK, or Bring Your Own Key, setup. The user obtains an API key from the Groq Console and enters it in AssistRecorder. The app stores that key locally in encrypted form.

Two transcription models are available: whisper-large-v3-turbo and whisper-large-v3. Language detection is automatic, so the recording language does not have to be selected manually before each request. Once transcription is complete, the text remains editable. The recording title can be edited as well, allowing recognition errors or unhelpful labels to be corrected before the next stage.

There are two important limits to account for. First, AssistRecorder does not automatically split a recording into chunks. A long file is not silently converted into several smaller requests. Second, Groq upload limits depend on the applicable plan. There is therefore no single fixed file-size assumption to rely on for every account. Users working with longer material should consult the conditions for their own Groq access and can trim a file beforehand when appropriate.

Processing the transcript in an LLM client

Speech-to-text produces an editable transcript, but a transcript and an organized deliverable are not the same thing. AssistRecorder provides prompt templates for meeting minutes, summaries, tasks, structured thoughts, parent conversations, and doctor conversations. Both template names and prompt contents can be changed.

Each template is an editable instruction. A user can inspect and revise it, while correcting names or specialist terms in the transcript before sharing.

When the content is ready, AssistRecorder uses Android ACTION_SEND to open the system sharing flow. The user then chooses an LLM client that can accept the shared text, for example ChatGPT, Claude, or Gemini. AssistRecorder does not select an embedded model, send the content to its own chat backend, or present itself as an LLM chat interface.

The chosen client creates the response under its own rules. It can be copied back into AssistRecorder, stored locally, and displayed as readable Markdown.

Templates for recurring situations

The meeting-minutes template provides a starting instruction for organizing a conversation. The summary template requests a shorter representation, the tasks template focuses on actionable items, and the structured-thoughts template applies to a less formal stream of ideas. They are starting points rather than fixed outputs.

Templates for parent and doctor conversations support workflows in which a spoken discussion needs to be reviewed in text. Such material may be sensitive, so it is especially important to inspect the transcript, consider the selected destination app, and check any generated result before using it further.

Editable names and prompts let users adapt these templates to recurring workflows.

Local storage and deliberate data transfers

AssistRecorder stores the audio, transcript, prompt, and any inserted AI result locally. However, local storage for these records should not be confused with an entirely offline workflow. Groq transcription requires an internet connection, and actively starting it sends the audio to Groq for speech recognition.

The LLM stage is separate. Prompt and transcript are shared only when the user invokes sharing and selects a destination. From that point onward, the destination app’s own privacy rules apply. This is relevant whether the chosen client is ChatGPT, Claude, Gemini, or another compatible LLM application.

The data flow can be summarized precisely:

• A locally stored recording is sent to Groq only after transcription is actively started.
• A prompt and transcript are sent onward only after the user actively shares them.
• An external result is stored in AssistRecorder only if the user inserts it there.
• Processing in the selected destination app is governed by that app’s privacy terms.

Sensitive material should be reviewed alongside the policies of each chosen external service.

Permissions and Android requirements

AssistRecorder is a native application for Android 10 and later. It uses microphone, notification, internet, and foreground-service permissions. The microphone is necessary to make a new recording. Internet access supports Groq transcription. Notifications and a foreground service are part of maintaining the recording operation within Android’s application model.

General storage permission is not needed for exporting a recording. Export and sharing are performed for the specifically selected content rather than through broad access to all device storage.

Installing an open-source release

AssistRecorder is open source, and its published builds are available through GitHub Releases. A release may currently offer a debug APK, so the assets shown on the latest release page should be checked before installation.

Because this is an installation outside Google Play, Android may require permission to install unknown apps from the relevant source. The exact prompt depends on the device and its settings. Android 10 or newer is required.

Transcription also requires the user’s own Groq API key. It can be created in the Groq Console, then entered into the app for encrypted local storage.

Boundaries to keep in mind

AssistRecorder provides a connected workflow, but it does not remove the constraints of the services involved:

• There is no automatic chunking for oversized or long audio files.
• Groq’s upload limits vary by plan.
• LLM processing happens in a separately selected client, not in an AssistRecorder chat.
• Transcripts, prompts, and external results remain material that the user can and should review.

Automatic language detection simplifies setup, but it does not guarantee that every name, term, or phrase will be represented as intended. The editable transcript is the place to resolve those issues before sharing it for further processing.

A brief technical view

AssistRecorder is built with Kotlin, Jetpack Compose, and Material 3. Room and DataStore support local persistence, while Android Keystore is used in the key-storage design. Hilt provides dependency injection and WorkManager handles background work. Retrofit and OkHttp cover network communication. Android’s MediaRecorder and MediaPlayer provide the recording and playback foundations.

Frequently asked questions

Does AssistRecorder automatically upload every recording?

No. Audio is sent to Groq only when the user actively starts transcription.

Which Groq models can transcribe the audio?

AssistRecorder supports whisper-large-v3-turbo and whisper-large-v3, with automatic language detection.

Where is the API key stored?

The user supplies a key from the Groq Console. AssistRecorder stores it locally in encrypted form.

Does the app split long recordings automatically?

No. It does not provide automatic chunking. Upload limits depend on the user’s Groq plan.

Is an LLM chat built into AssistRecorder?

No. Prompt and transcript are shared via Android ACTION_SEND to a client selected by the user, such as ChatGPT, Claude, or Gemini.

Can I keep an external AI result?

Yes. It can be inserted, stored locally, and read as Markdown.

Conclusion

AssistRecorder connects controlled Android steps: record or import M4A audio, request Groq transcription with your own key, edit it, then share it with an editable prompt to a selected LLM app. Plan limits, absent automatic chunking, external LLM processing, and the destination’s privacy rules remain explicit.