Updated ctc-segmentation Python package version
This PR updates the `ctc-segmentation` Python package used for the CTC segmentation tool from version 1.1.0 to 1.4.0. The update provides a bugfix, as well as sane defaults, which results in better alignments.

I would also recommend the latest version, however, the interface changed at two points:

1. As not every ASR architecture uses subsampling, I replaced the `subsampling` and `frame_duration` parameters with a new parameter `index_duration`. This parameter can simply be calculated as `frame_duration_ms * subsampling_factor / 1000`.
2. The text can now be given as a token ID sequence obtained from the tokenizer (which is already integrated into Nemo). The text input was chosen for our initial implementation, because our ASR model had long tokens and it made sense to scan for partial tokens. As the pre-trained Nemo models are already character-based, scanning for partial tokens is not necessary; using this method will improve alignment speed and probably also generate better alignments (because the pre-processing of the text may be better with a tokenizer).

@ekmb 