# Advancing Spanish Speech Emotion Recognition: A Comprehensive Benchmark of Pre-Trained Models
## 3 Materials and Methods
### Databases
The recordings were conducted in a professional studio, and the audio was sampled at 48,000 Hz with 16-bit resolution. Each adult participant recorded48 words per emotion, while children recorded 24 words per emotion. The database was validated in [72] using an SVM model, and an accuracy of 93.9% for men, 89.4% for women, and 83.3% for children was achieved
3. Spanish MEACorpus. The Spanish MEACorpus [68] is a multimodal database created in 2022, containing 5129 audio segments extracted from 13.16 h of Spanish speech. The emotional distribution is based on [PERSON]'s basic emotions. The segments are derived from YouTube videos, with natural settings such as political speeches, sports events, and entertainment shows being captured and recorded spontaneously. The database includes 46% female voices and 54% male voices, though specific details on speaker ages are not provided. The audios are in WAV format at a sampling rate of 44,100 Hz, with an average length of 9.24 s, segmented using a noise and silence threshold-based algorithm. Manual annotation was performed by three annotators, with [PERSON]'s taxonomy being used. 4. EmoWisconsin. EmoWisconsin [66] was created in 2011 in Mexican Spanish and contains 3098 segments of children's speech, including 28 participants (17 boys and 11 girls) aged 7 to 13. The labeled emotions include six categories: Annoyed, Motivated, Nervous, Neutral, Doubtful, and Confident, along with the three continuous primitives of valence, arousal, and dominance. The recordings were made at 44,100 Hz in 16-bit PCM WAV format, totaling 11 h and 39 min of recordings across 56 sessions. Emotions were elicited using a modified version of the Wisconsin Card Sorting Test (WCST), with sessions divided into positive and negative interactions. 5. INTERFACE (INTERISP). The INTERFACE [73] database was created in 2002 and contains 5520 samples in Spanish (INTERISP), along with recordings in English, Slovenian, and French. Six emotions are included: anger, sadness, joy, fear, disgust, and surprise. Additionally, neutral speech styles were recorded in Spanish, including variations like soft, loud, slow, and fast. Recordings were made by one professional actor and one actress in each language. For validation, 18 non-professional listeners evaluated 56 statements through subjective tests. Recognition accuracy in the first choice exceeded 80%, rising to 90% when a second option was included. This database is available in the ELRA repository [79]. 6. EmoFilm. EmoFilm [74] is a multilingual database created in 2018, designed to enrich underrepresented languages such as Spanish, Italian, and others. It consists of 1115 clips with an average length of 3.5 s, distributed as 360 clips in English, 413 in Italian, and 342 in Spanish. This dataset includes five emotions: anger, sadness, happiness, fear, and contempt. For this study, only the Spanish portion of EmoFilm was used (EmoFilm\({}_{ES}\)). Movie and TV series clips have been extracted, capturing emotional expressions in acted contexts. Emotion annotation was performed through evaluations by multiple annotators, achieving high perceptual reliability.