def get_parts_of_speech(prod_desc):

    tokenizer = RegexpTokenizer(r'\w+')
    tokens = tokenizer.tokenize(prod_desc)
    text = nltk.Text(tokens)
    tagged = nltk.pos_tag(text, tagset='universal')

    counts = Counter(tag for word,tag in tagged)
    for word, tag in tagged:
        counts[tag] += 1
    total = sum(counts.values())
    counts_norm = dict((word, float(count)/total) for word,count in counts.items())

    return counts_norm