# talk

## Overview

An R-package for analyzing natural language with transformers-based
large language models. The `talk` package is part of the *R Language
Analysis Suite*, including `talk`, `text` and `topics`.

- [`talk`](https://www.r-talk.org/) transforms voice recordings into
  text, audio features, or embeddings.  
    
- [`text`](https://www.r-text.org/) provide many language tasks such as
  converting digital text into word embeddings.  
    
  `talk` and `text` provide access to Large Language Models from Hugging
  Face.  
    
- [`topics`](https://www.r-topics.org/) visualizes language patterns
  into topics to generate psychological insights.  
    
    
  ![](reference/figures/talk_text_topics1.svg)

  
The *R Language Analysis Suite* is created through a collaboration
between psychology and computer science to address research needs and
ensure state-of-the-art techniques. The suite is continuously tested on
Ubuntu, Mac OS and Windows using the latest stable R version.

> ### 📣 Online Workshop: *Analysing Human Language using R*
>
> **August 11–13, 2026** — three half-day sessions (2:00–5:00 pm CEST /
> 8:00–11:00 am ET)
>
> Learn the full *R Language Analysis Suite* —
> [`talk`](https://www.r-talk.org/), [`text`](https://www.r-text.org/),
> and [`topics`](https://www.r-topics.org/) — with Oscar Kjell.
>
> **[Read more & register →](https://smart-workshops.com/lang-r-info)**

### Point solution for transforming talk to embeddings

Recent advances in speech and language modelling have dramatically
improved how well computers can transcribe and represent human speech.
The talk-package makes these state-of-the-art models — such as Whisper
from [HuggingFace](https://huggingface.co/docs/transformers/index) —
easily accessible from R. All analyses run locally on your own computer,
so recordings never leave your machine — important when working with
sensitive data such as clinical or research interviews.

With talk you can:

- **Transcribe speech to text**: turn audio recordings into text, in
  many languages.
- **Identify who says what and when**: split a conversation by speaker,
  with time-stamped speaker turns (diarisation).
- **Transform speech into embeddings**: represent whole recordings — or
  each speaker turn — as numeric vectors that capture acoustic and
  psychologically relevant properties of the voice, beyond the words
  themselves.
- **Use the embeddings in downstream analyses**: for example, training
  models to predict psychological constructs with the
  [text](https://www.r-text.org/)-package.

See the [Getting started
tutorial](https://www.r-talk.org/articles/talk.html) for a walk-through
of the workflow, and [HuggingFace](https://huggingface.co/models/) for
the available models.

# Package index

## Installation

- [`talkrpp_install()`](https://r-talk.org/reference/talkrpp_install.md)
  [`talkrpp_install_virtualenv()`](https://r-talk.org/reference/talkrpp_install.md)
  : Install talk required python packages in conda or virtualenv
  environment
- [`talkrpp_uninstall()`](https://r-talk.org/reference/talkrpp_uninstall.md)
  : Uninstall talkrpp conda environment
- [`talkrpp_initialize()`](https://r-talk.org/reference/talkrpp_initialize.md)
  : Initialize talk required python packages
- [`find_talkrpp_env()`](https://r-talk.org/reference/find_talkrpp_env.md)
  : Find talk required python packages env
- [`list_talkrpp_envs()`](https://r-talk.org/reference/list_talkrpp_envs.md)
  : List available Python environments

## Transform talk to word embeddings

- [`talkText()`](https://r-talk.org/reference/talkText.md)
  [`talkTranscribe()`](https://r-talk.org/reference/talkText.md) :
  Transcribe audio recordings to text (speech-to-text)
- [`talkEmbed()`](https://r-talk.org/reference/talkEmbed.md) : Transform
  audio recordings to embeddings
- [`talkTranscribeDiarise()`](https://r-talk.org/reference/talkTranscribeDiarise.md)
  [`talkTextDiarise()`](https://r-talk.org/reference/talkTranscribeDiarise.md)
  : Transcribe and Diarize Audio Recordings
- [`talkEmbedSegments()`](https://r-talk.org/reference/talkEmbedSegments.md)
  : Transform diarized audio into segment-level embeddings

# Articles

### All vignettes

- [Extended Installation
  Guide](https://r-talk.org/articles/talk_huggingface_in_r_extended_installation_guide.md):

- [Getting started](https://r-talk.org/articles/talk.md):

  Introduction to talk: HuggingFace transformers in R.