# An Overview of the IberSpeech-RTVE 2022 Challenges on Speech Technologies
## 5 IberSpeech-RTVE 2022 Results and Discussion  
### Speech to Text Challenge  
Table 10 presents the overall results for the RTVE2022 DB test dataset. The more competitive systems have been the ones submitted by BCN2 BRNO and VICOM-UPM teams. The best results have been obtained by the BCN2 BRNO team, where their primary system (a fusion of 5 individual models) achieves a word error rate of 14.35%. It is worth noting the good results of the VICOM-UPM team, as their first contrastive system based on a pruned RNN-Transducer model obtains a remarkable 14.78% WER. Two contrastive systems are based on the large model of the Whisper engine. Although the data and models are the same, there is a significant difference between the final WER obtained by both submissions. The post-processing strategy of the BCN2 BRNO team was based on using _zlib_ to compress the segment transcripts and filter out segments with a compression factor higher than 2. The VICOM-UPM team used a more sophisticated post-processing strategy: for transcriptions where more than 20% of segments were text repetitions, the audio was segmented through a VAD module, non-speech segments longer than 2 s were discarded and the decoding was remade. The decoding process of the rest of the speech segments was performed by resetting the pre-condition of the text decoder. In addition, text phrases repeated three times or more were filtered out and only a single appearance was kept. The best WER obtained by a Whisper-based system was 14.87% for the VICOM-UPM approach. It is interesting to study the distribution of WER in terms of the different shows that make up the test set. Table 11 presents the best results by show, that is, for each show the system with the lowest WER has been taken. It is remarkable that 12 out of 21 shows have a WER below 15%, the lowest WER of 5.89% being found for the Agrosfera (AG) show. The three serial dramas, Grasa (GR), Riders (RD) and Yreal (YR) are in the range of 18% to 25% WER. In the Grasa serial drama, most of the players are using Spanish Slang typical of the drug world which makes noteworthy the 24.79% WER. The show EE (indoor interviews) is composed of raw footage of interviews where the cameraman, producer and other people besides the interviewee are talking with a low signal-to-noise ratio, which makes WER rise to 22.2% from the expected 10%. Finally, the worst WER, 47.79%, is obtained for the APB (A Pedir de Boca) show. The audio of this show comes from raw footage where some interviewees are using Spanish Slang, and most of the time people behind the cameras are asking questions or talking, which has made also hard for human annotators to transcribe these materials. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**System ID** & **Primary** & **C1** & **C2** & **C3** \\ \hline BCN2 BRNO & 14.35\% & 15.24\% & 17.22\% & 18.65\% \\ \hline TID & 23.50\% & 23.45\% & 24.87\% & 25.25\% \\ \hline VICOM-UPM & 15.30\% & 14.78\% & 17.29\% & 14.87\% \\ \hline UZ & 20.32\% & 26.49\% & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Speech to Text challenge results for the RTVE2022 DB test dataset. Three shows have been used in previous challenges: CA (Comando Actualidad) and AT (Aqui la Tierra) in 2022 and SyG (Saber y Ganar) in 2018. Table 12 shows the comparison among the 3 last challenges for the three shows and the best system WER over the whole test set. It is noteworthy the significant improvement in WER observed in the three shows and in the whole test set. In the latter case, there is a 10% improvement between the 2020 and 2022 challenges although the organization has tried to rise the difficulty including audio recordings from shows with only raw footage and Spanish Slang. The increase in difficulty is clear if we compare the results obtained in 2020 and 2022 using the Whisper model.