Translations:Tools voor het geautomatiseerd transcriberen van audio- en videofragmenten/8/en

You can take into account a number of factors to achieve better results:

• The strength of the speech recognition tools depends on the model used: e.g., which languages does the model support and how well can the model handle dialects or colloquial language? The choice for the model depends on the needs and use cases, such as the trade-off between speed and accuracy, and the language that must be transcribed. In the overview we chose accuracy (it is important that the text is correct than that the tool is fast) and Dutch as colloquial language. They were also all tested on interviews in which slight dialect or intermediate language was spoken. The most accurate tools scored well for this, but generally it was noted that interviews with pronounced dialects resulted in poorer transcriptions.
• Another important point of attention is the quality of the recording. Recordings with clear sound and without background noise give better results than recordings with poor sound quality (e.g. noise) and background noise. Speakers who speak clearly are also transcribed better than speakers who mumble.
• Desktop applications use the computing power of the computer when transcribing the text. If your computer has a dedicated GPU, the transcription will proceed much faster. A dedicated GPU is a special GPU with its own card connected to the motherboard, while an integrated GPU is embedded in the same chip as the CPU. This article (in Dutch) explains more about the different GPUs. If your computer does not have this GPU, then the CPU or processor is used. This is slower. You can also use an online service so that you are not limited by the limits of your computer.