Update app.py

app.py

@@ -23,14 +23,17 @@ def predict_and_ctc_lm_decode(input_file):
     transcribed_text = asr(speech, chunk_length_s=10, stride_length_s=1)["text"]
     pipe2 = pipeline("text-classification", model = "hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021")
     sexism_detection = pipe2(transcribed_text)[0]['label']
+    if sexism_detection == "LABEL_0":
+        return "The input audio contains NON-SEXIST language"
+    else:
+        return "SEXIST LANGUAGE DETECTED"
 
-    return sexism_detection
 
 description = """ This is a Gradio demo for Spanish audio transcription-based Sexism detection. To use this, simply provide an audio input (audio recording or via microphone), which will subsequently be transcribed and classified as sexism/non-sexism pertaining to audio (transcription) with the help of pre-trained models.
 
 
 
-**NOTE regarding the predicted label: LABEL_0: "NON SEXISM" or LABEL_1: "SEXISM"**
+**Note regarding the predicted label: LABEL_0: "NON SEXISM" or LABEL_1: "SEXISM"**
 
 
 
@@ -38,7 +41,6 @@ Pre-trained Model used for Spanish ASR: [jonatasgrosman/wav2vec2-xls-r-1b-spanis
 
 Pre-trained Model used for Sexism Detection : [hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021](https://huggingface.co/hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021)
 
-Observation: To produce reliable results, the aforementioned pre-trained model for sexism detection requires some more training.
 """