Normalizer and NormalizerWithAudio fail with dashed tokens eg "550-pound bomb"
The taggers pick these examples up as Serials and not as Measures. The options with the spaces between the letters make sense if it's a Serial.

I think a modification to the tagger for Measure that allows the dash between Cardinal and Unit may do the trick. If I can figure out the syntax... Yes, this is a known issue, the fix is a part of the upcoming update. 
I'll update this bug when the PR is ready. I'll be following the progress closely and am happy to help if I can get more familiar with pynini -- is this repo the best place to file / discuss similar issues?
**Describe the bug**

Example sentence fragments for text normalizer:
"It had 12-inch guns and a 21-knot cruising speed."
"Each 550-pound bomb exploded."

**Steps/Code to reproduce bug**

```python
from nemo_text_processing.text_normalization.normalize import Normalizer
from nemo_text_processing.text_normalization.normalize_with_audio import NormalizerWithAudio

normalizer = Normalizer(input_case='cased')
audio_normalizer = NormalizerWithAudio(input_case='cased')

texts = [
    "It had 12-inch guns and a 21-knot cruising speed.",
    "Each 550-pound bomb exploded.",
]

for text in texts:
    normalized_text = normalizer.normalize(text, verbose=False)
    print(normalized_text)

    normalized_texts = audio_normalizer.normalize_with_audio(text, verbose=False)
    print(normalized_texts)
```
The results from normalized_texts will be something like (notice the spaces between each letter in the word for the units):
"five hundred fifty p o u n d bomb"
and
"twenty one k n o t cruising speed"

It seems like the sparrow/pynini rules don't allow for dashed text input followed by a unit and interpret the unit as an abbreviation. The CER calculation in NormalizerWithAudio doesn't repair this because the results from normalize_with_audio() don't ever contain the expected outputs.

**Expected behavior**

"five hundred fifty pound bomb"
"twenty one knot cruising speed"

**Environment overview (please complete the following information)**

 - Environment location: Bare-metal
 - Method of NeMo install: pip install from source, main branch

**Environment details**

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version Ubuntu 20.10
- PyTorch version 1.7.1
- Python version 3.8.5

I'm trying to track down where in pynini or the nemo rules this is happening and if I find it I will follow-up.